This report prints the restuls tables from estimated models

Relies on the previous execution of the following scripts: - ./reports/report-governor - ./models/../compile-models.R - ./models/../compile-tables.R

# prepared by Ellis Island and ./reports/report-governor.R
dto <- readRDS("./data/unshared/derived/dto_h.rds")

# prepared by ../compile-models.R
models_pooled <- readRDS("./data/shared/derived/models/models_pooled.rds")#  glm objects
subset_pooled <- readRDS("./data/shared/derived/models/subset_pooled.rds")#  glmulti objects

models_local <- readRDS("./data/shared/derived/models/models_local.rds")
subset_local <- readRDS("./data/shared/derived/models/subset_local.rds")

# prepared by ../compile-tables.R
tables_pooled <- readRDS("./data/shared/derived/tables/tables_pooled.rds")
tables_bw_pooled <- readRDS("./data/shared/derived/tables/tables_bw_pooled.rds")
tables_local <- readRDS("./data/shared/derived/tables/tables_local.rds")
tables_bw_local <- readRDS("./data/shared/derived/tables/tables_bw_local.rds")

ds_within <- readRDS("./data/shared/derived/tables/ds_within.rds")
ds_between <- readRDS("./data/shared/derived/tables/ds_between.rds")

Guide to Models

Each of the following models (A, B, AA, and BB) are fitted to the data from each study separately. When fitted to the pooled data, an additional predictor, study_name is added after the intercept.

predictors/model A B AA BB best
age age_in_years_70 age_in_years_70 age_in_years_70 age_in_years_70 ?
sex female female female female ?
education educ3 educ3 educ3 educ3 ?
marital status single single single single ?
health poor_health poor_health ?
physical activity sedentary sedentary ?
employment current_work current_work ?
alcohol use current_drink_2 current_drink_2 ?
INTERACTIONS NONE NONE ALL PAIRWISE ALL PAIRWISE ?

Odds-ratios with 95% confidence intervals are reported. The model labeled “best” represents the solution suggested by the top ranked model from the best subset search propelled by genetic algorithm with AICC as the guiding selection criteria.

Dynamic tables

Between models

The following table reports comparison across five model types (A, B, AA, BB, best) and six datasets (alsa, lbsl, satsa, share, tilda, pooled). You can think of this as multiple tables stacked on top of each other. You select a single table by choosing the value for study_name. (you may need to adjust the number of entries to view, at the top left of the dynamic table).

Within models

The following table reports estimates and odds from every model that has been fit during the exercise. You can think of this as multiple tables of various heights stacked on top of each other. You select a single table by chosing the values for study_name and model_type. (you may need to adjust the number of entries to view, at the top left of the dynamic table)

Static tables

pooled

BETWEEN

coef_name A B AA BB best
(Intercept) .16(.14,.19)*** .1(.08,.12)*** .16(.13,.19)*** .11(.08,.16)*** .12(.08,.19)***
study_name_f(LBLS) .86(.63,1.15) .93(.68,1.26) .99(.72,1.35) 1.06(.76,1.45) .75(.3,1.8)
study_name_f(SATSA) 1.32(1.05,1.65)* 1.24(.98,1.55). 1.47(1.17,1.86)** 1.26(.99,1.61). .56(.24,1.26)
study_name_f(SHARE) .91(.75,1.11) 1.14(.93,1.41) 1.04(.84,1.28) 1.2(.96,1.51) 1.33(.77,2.31)
study_name_f(TILDA) .85(.71,1.03). .97(.8,1.18) .95(.78,1.17) 1.03(.83,1.27) .61(.36,1.04).
age_in_years_70 .96(.96,.97)*** .96(.95,.96)*** .97(.96,.99)*** .97(.96,.99)** .96(.93,.98)***
femaleTRUE .81(.73,.89)*** .81(.73,.9)*** .77(.62,.94)* .78(.59,1.03). .67(.49,.92)*
educ3_f( < HS ) 1.22(1.08,1.37)*** 1.18(1.05,1.32)** 1.14(.94,1.38) .97(.72,1.31) 1.28(.8,2.03)
educ3_f( HS < ) .77(.66,.91)** .8(.68,.93)** .77(.6,.99)* .87(.59,1.28) .94(.61,1.46)
singleTRUE 1.48(1.33,1.65)*** 1.49(1.33,1.66)*** 1.4(1.1,1.78)** 1.35(.97,1.87). 1.4(1,1.95)*
poor_healthTRUE 1.26(1.13,1.4)*** 1.29(.95,1.74). 1.35(.92,1.96)
sedentaryTRUE 1.45(1.29,1.62)*** 1.4(1.02,1.92)* 1.28(.94,1.75)
current_work_2TRUE .71(.63,.81)*** .82(.56,1.2) 2.25(.8,5.41).
current_drinkTRUE 1.53(1.36,1.71)*** 1.26(.96,1.67). 1.35(.94,1.96)
age_in_years_70:femaleTRUE .98(.97,.99)*** .99(.98,1)* .98(.97,.99)***
age_in_years_70:educ3_f( < HS ) 1(.99,1.01) 1(.98,1.01)
age_in_years_70:educ3_f( HS < ) 1.02(1.01,1.04)** 1.02(1,1.03)
age_in_years_70:singleTRUE .99(.98,1)* .99(.98,1)
age_in_years_70:poor_healthTRUE 1(.99,1.01)
age_in_years_70:sedentaryTRUE 1(.98,1.01)
age_in_years_70:current_work_2TRUE 1.01(.99,1.02)
age_in_years_70:current_drinkTRUE .99(.98,1).
femaleTRUE:educ3_f( < HS ) .96(.77,1.21) .98(.78,1.24)
femaleTRUE:educ3_f( HS < ) 1.2(.87,1.65) 1.18(.85,1.63)
femaleTRUE:singleTRUE .85(.68,1.06) .9(.72,1.13)
femaleTRUE:poor_healthTRUE 1.06(.85,1.33)
femaleTRUE:sedentaryTRUE .84(.67,1.05)
femaleTRUE:current_work_2TRUE 1.19(.91,1.54)
femaleTRUE:current_drinkTRUE .95(.76,1.18)
educ3_f( < HS ):singleTRUE 1.23(.95,1.58) 1.26(.97,1.63).
educ3_f( HS < ):singleTRUE 1(.71,1.41) .99(.7,1.41)
educ3_f( < HS ):poor_healthTRUE 1.33(1.03,1.71)* 1.29(.98,1.69).
educ3_f( HS < ):poor_healthTRUE .86(.61,1.22) .87(.59,1.26)
educ3_f( < HS ):sedentaryTRUE 1.16(.9,1.51)
educ3_f( HS < ):sedentaryTRUE 1.05(.73,1.49)
educ3_f( < HS ):current_work_2TRUE .88(.67,1.17) .89(.68,1.15)
educ3_f( HS < ):current_work_2TRUE .82(.54,1.25) .63(.42,.94)*
educ3_f( < HS ):current_drinkTRUE 1.01(.79,1.3) .77(.59,1.02).
educ3_f( HS < ):current_drinkTRUE .99(.71,1.38) 1.23(.85,1.79)
singleTRUE:poor_healthTRUE .83(.65,1.05) .83(.66,1.05)
singleTRUE:sedentaryTRUE .89(.69,1.14)
singleTRUE:current_work_2TRUE .92(.69,1.23)
singleTRUE:current_drinkTRUE 1.24(.98,1.58).
poor_healthTRUE:sedentaryTRUE .76(.6,.96)* .76(.59,.96)*
poor_healthTRUE:current_work_2TRUE .82(.62,1.09) .81(.63,1.05)
poor_healthTRUE:current_drinkTRUE 1.03(.83,1.3)
sedentaryTRUE:current_work_2TRUE 1.15(.86,1.53)
sedentaryTRUE:current_drinkTRUE 1.2(.95,1.51)
current_work_2TRUE:current_drinkTRUE .99(.76,1.31)

A

solution of model A fit to combined and harmonized data from ALL studies

logLik dev AIC BIC df_Null df_Model df_drop
-5326.851 10653.7 10673.7 10747.9 12327 12318 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .16 (.14,.19) -1.82 .09 0.0000 <=.001
study_name_f(LBLS) .86 (.63,1.15) -.16 .16 0.3147 > .10
* study_name_f(SATSA) 1.32 (1.05,1.65) .28 .11 0.0162 <=.05
study_name_f(SHARE) .85 (.69,1.04) -.17 .1 0.1029 > .10
. study_name_f(TILDA) .85 (.71,1.03) -.16 .1 0.0979 <=.10
*** age_in_years_70 .96 (.96,.97) -.04 0 0.0000 <=.001
*** femaleTRUE .81 (.73,.89) -.21 .05 0.0000 <=.001
*** educ3_f( < HS ) 1.22 (1.08,1.37) .2 .06 0.0010 <=.001
** educ3_f( HS < ) .77 (.66,.91) -.26 .08 0.0019 <=.01
*** singleTRUE 1.48 (1.33,1.65) .39 .06 0.0000 <=.001

B

solution of model B fit to combined and harmonized data from ALL studies

logLik dev AIC BIC df_Null df_Model df_drop
-5258.86 10517.72 10545.7 10649.6 12327 12314 13
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .1 (.08,.12) -2.29 .11 0.0000 <=.001
study_name_f(LBLS) .93 (.68,1.26) -.07 .16 0.6513 > .10
. study_name_f(SATSA) 1.24 (.98,1.55) .21 .12 0.0687 <=.10
study_name_f(SHARE) 1.04 (.85,1.29) .04 .11 0.6868 > .10
study_name_f(TILDA) .97 (.8,1.18) -.03 .1 0.7660 > .10
*** age_in_years_70 .96 (.95,.96) -.05 0 0.0000 <=.001
*** femaleTRUE .81 (.73,.9) -.21 .05 0.0000 <=.001
** educ3_f( < HS ) 1.18 (1.05,1.32) .16 .06 0.0068 <=.01
** educ3_f( HS < ) .8 (.68,.93) -.23 .08 0.0054 <=.01
*** singleTRUE 1.49 (1.33,1.66) .4 .06 0.0000 <=.001
*** poor_healthTRUE 1.26 (1.13,1.4) .23 .06 0.0000 <=.001
*** sedentaryTRUE 1.45 (1.29,1.62) .37 .06 0.0000 <=.001
*** current_work_2TRUE .71 (.63,.81) -.34 .06 0.0000 <=.001
*** current_drinkTRUE 1.53 (1.36,1.71) .42 .06 0.0000 <=.001

AA

solution of model AA fit to combined and harmonized data from ALL studies

logLik dev AIC BIC df_Null df_Model df_drop
-5308.01 10616.02 10654 10795 12327 12309 18
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .16 (.13,.19) -1.85 .1 0.0000 <=.001
study_name_f(LBLS) .98 (.72,1.34) -.02 .16 0.9165 > .10
** study_name_f(SATSA) 1.48 (1.17,1.87) .39 .12 0.0011 <=.01
study_name_f(SHARE) .97 (.78,1.2) -.03 .11 0.7592 > .10
study_name_f(TILDA) .95 (.78,1.17) -.05 .1 0.6355 > .10
*** age_in_years_70 .97 (.96,.98) -.03 .01 0.0000 <=.001
** femaleTRUE .76 (.61,.93) -.28 .11 0.0085 <=.01
educ3_f( < HS ) 1.13 (.93,1.38) .13 .1 0.2101 > .10
. educ3_f( HS < ) .79 (.61,1.01) -.24 .13 0.0573 <=.10
** singleTRUE 1.4 (1.09,1.78) .34 .12 0.0068 <=.01
*** age_in_years_70:femaleTRUE .98 (.97,.99) -.02 0 0.0003 <=.001
age_in_years_70:educ3_f( < HS ) 1 (.99,1.01) 0 .01 0.5561 > .10
** age_in_years_70:educ3_f( HS < ) 1.02 (1.01,1.03) .02 .01 0.0055 <=.01
* age_in_years_70:singleTRUE .99 (.98,1) -.01 0 0.0492 <=.05
femaleTRUE:educ3_f( < HS ) .97 (.77,1.21) -.03 .11 0.7734 > .10
femaleTRUE:educ3_f( HS < ) 1.19 (.87,1.64) .17 .16 0.2837 > .10
femaleTRUE:singleTRUE .85 (.68,1.06) -.16 .11 0.1525 > .10
educ3_f( < HS ):singleTRUE 1.23 (.95,1.58) .2 .13 0.1111 > .10
educ3_f( HS < ):singleTRUE 1 (.7,1.41) 0 .18 0.9885 > .10

BB

solution of model BB fit to combined and harmonized data from ALL studies

logLik dev AIC BIC df_Null df_Model df_drop
-5221.406 10442.81 10540.8 10904.4 12327 12279 48
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .11 (.08,.16) -2.17 .17 0.0000 <=.001
study_name_f(LBLS) 1.05 (.76,1.43) .04 .16 0.7829 > .10
. study_name_f(SATSA) 1.26 (.99,1.61) .23 .13 0.0659 <=.10
study_name_f(SHARE) 1.1 (.88,1.39) .1 .12 0.4007 > .10
study_name_f(TILDA) 1.03 (.83,1.27) .03 .11 0.8043 > .10
*** age_in_years_70 .97 (.95,.99) -.03 .01 0.0007 <=.001
. femaleTRUE .77 (.58,1.01) -.26 .14 0.0610 <=.10
educ3_f( < HS ) .97 (.72,1.31) -.03 .15 0.8408 > .10
educ3_f( HS < ) .89 (.61,1.31) -.11 .2 0.5667 > .10
. singleTRUE 1.35 (.97,1.86) .3 .17 0.0746 <=.10
. poor_healthTRUE 1.3 (.96,1.75) .26 .15 0.0882 <=.10
* sedentaryTRUE 1.4 (1.01,1.92) .33 .16 0.0408 <=.05
current_work_2TRUE .82 (.56,1.2) -.2 .2 0.3020 > .10
current_drinkTRUE 1.25 (.95,1.65) .22 .14 0.1184 > .10
* age_in_years_70:femaleTRUE .99 (.98,1) -.01 .01 0.0245 <=.05
age_in_years_70:educ3_f( < HS ) 1 (.98,1.01) 0 .01 0.5821 > .10
age_in_years_70:educ3_f( HS < ) 1.01 (1,1.03) .01 .01 0.1425 > .10
age_in_years_70:singleTRUE .99 (.98,1.01) -.01 .01 0.2926 > .10
age_in_years_70:poor_healthTRUE 1 (.99,1.01) 0 .01 0.6316 > .10
age_in_years_70:sedentaryTRUE 1 (.98,1.01) 0 .01 0.5225 > .10
age_in_years_70:current_work_2TRUE 1.01 (.99,1.02) .01 .01 0.3672 > .10
. age_in_years_70:current_drinkTRUE .99 (.98,1) -.01 .01 0.0899 <=.10
femaleTRUE:educ3_f( < HS ) .99 (.78,1.24) -.01 .12 0.9049 > .10
femaleTRUE:educ3_f( HS < ) 1.17 (.85,1.61) .16 .16 0.3414 > .10
femaleTRUE:singleTRUE .9 (.72,1.13) -.1 .12 0.3702 > .10
femaleTRUE:poor_healthTRUE 1.06 (.85,1.33) .06 .11 0.5916 > .10
femaleTRUE:sedentaryTRUE .84 (.67,1.05) -.17 .11 0.1330 > .10
femaleTRUE:current_work_2TRUE 1.19 (.91,1.54) .17 .13 0.1983 > .10
femaleTRUE:current_drinkTRUE .95 (.77,1.18) -.05 .11 0.6647 > .10
. educ3_f( < HS ):singleTRUE 1.26 (.97,1.63) .23 .13 0.0817 <=.10
educ3_f( HS < ):singleTRUE .99 (.7,1.4) -.01 .18 0.9501 > .10
* educ3_f( < HS ):poor_healthTRUE 1.33 (1.03,1.71) .28 .13 0.0279 <=.05
educ3_f( HS < ):poor_healthTRUE .86 (.61,1.22) -.15 .18 0.4105 > .10
educ3_f( < HS ):sedentaryTRUE 1.17 (.9,1.51) .15 .13 0.2488 > .10
educ3_f( HS < ):sedentaryTRUE 1.05 (.73,1.49) .05 .18 0.7971 > .10
educ3_f( < HS ):current_work_2TRUE .89 (.67,1.17) -.12 .14 0.3982 > .10
educ3_f( HS < ):current_work_2TRUE .81 (.53,1.23) -.21 .22 0.3220 > .10
educ3_f( < HS ):current_drinkTRUE 1.02 (.8,1.3) .02 .13 0.8742 > .10
educ3_f( HS < ):current_drinkTRUE .98 (.71,1.37) -.02 .17 0.9217 > .10
singleTRUE:poor_healthTRUE .82 (.65,1.04) -.2 .12 0.1022 > .10
singleTRUE:sedentaryTRUE .89 (.69,1.14) -.12 .13 0.3496 > .10
singleTRUE:current_work_2TRUE .93 (.7,1.25) -.07 .15 0.6386 > .10
. singleTRUE:current_drinkTRUE 1.25 (.99,1.59) .22 .12 0.0672 <=.10
* poor_healthTRUE:sedentaryTRUE .76 (.6,.96) -.28 .12 0.0200 <=.05
poor_healthTRUE:current_work_2TRUE .83 (.63,1.11) -.18 .15 0.2173 > .10
poor_healthTRUE:current_drinkTRUE 1.03 (.82,1.29) .03 .11 0.7887 > .10
sedentaryTRUE:current_work_2TRUE 1.15 (.86,1.53) .14 .15 0.3333 > .10
sedentaryTRUE:current_drinkTRUE 1.2 (.96,1.52) .19 .12 0.1158 > .10
current_work_2TRUE:current_drinkTRUE .99 (.75,1.3) -.01 .14 0.9172 > .10

best

solution of model best fit to combined and harmonized data from ALL studies

logLik dev AIC BIC df_Null df_Model df_drop
-5143.964 10287.93 10407.9 10853.1 12327 12268 59
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .12 (.08,.19) -2.1 .24 0.0000 <=.001
study_name_f(LBLS) .75 (.3,1.8) -.29 .45 0.5297 > .10
study_name_f(SATSA) .56 (.24,1.26) -.58 .42 0.1644 > .10
study_name_f(SHARE) 1.36 (.79,2.37) .31 .28 0.2682 > .10
. study_name_f(TILDA) .61 (.36,1.04) -.5 .27 0.0647 <=.10
educ3_f( < HS ) 1.28 (.8,2.03) .25 .24 0.2933 > .10
educ3_f( HS < ) .94 (.61,1.46) -.06 .22 0.7940 > .10
*** age_in_years_70 .96 (.93,.98) -.04 .01 0.0008 <=.001
* femaleTRUE .67 (.49,.92) -.39 .16 0.0141 <=.05
* singleTRUE 1.4 (1,1.95) .34 .17 0.0486 <=.05
poor_healthTRUE 1.35 (.92,1.96) .3 .19 0.1241 > .10
sedentaryTRUE 1.28 (.94,1.75) .25 .16 0.1169 > .10
. current_work_2TRUE 2.25 (.8,5.41) .81 .48 0.0905 <=.10
current_drinkTRUE 1.35 (.94,1.96) .3 .19 0.1113 > .10
study_name_f(LBLS):educ3_f( < HS ) 1.33 (.5,3.46) .29 .49 0.5555 > .10
study_name_f(SATSA):educ3_f( < HS ) 1.16 (.6,2.31) .15 .34 0.6570 > .10
study_name_f(SHARE):educ3_f( < HS ) .81 (.5,1.35) -.21 .25 0.4194 > .10
study_name_f(TILDA):educ3_f( < HS ) 1.12 (.71,1.77) .11 .23 0.6326 > .10
study_name_f(LBLS):educ3_f( HS < ) 1.11 (.54,2.32) .1 .37 0.7807 > .10
study_name_f(SATSA):educ3_f( HS < ) 1.29 (.58,2.87) .26 .41 0.5244 > .10
study_name_f(SHARE):educ3_f( HS < ) 1.08 (.66,1.75) .07 .25 0.7619 > .10
** study_name_f(TILDA):educ3_f( HS < ) .47 (.26,.81) -.76 .29 0.0079 <=.01
*** age_in_years_70:femaleTRUE .98 (.97,.99) -.02 .01 0.0001 <=.001
singleTRUE:poor_healthTRUE .83 (.66,1.05) -.18 .12 0.1165 > .10
* poor_healthTRUE:sedentaryTRUE .76 (.59,.96) -.28 .12 0.0220 <=.05
poor_healthTRUE:current_work_2TRUE .81 (.63,1.05) -.21 .13 0.1209 > .10
study_name_f(LBLS):age_in_years_70 1.02 (.99,1.06) .02 .02 0.2339 > .10
study_name_f(SATSA):age_in_years_70 1 (.97,1.03) 0 .02 0.9971 > .10
*** study_name_f(SHARE):age_in_years_70 1.06 (1.03,1.09) .06 .01 0.0001 <=.001
study_name_f(TILDA):age_in_years_70 1 (.97,1.02) 0 .01 0.7631 > .10
. study_name_f(LBLS):femaleTRUE 1.83 (.95,3.53) .6 .33 0.0710 <=.10
* study_name_f(SATSA):femaleTRUE .57 (.37,.89) -.56 .23 0.0143 <=.05
study_name_f(SHARE):femaleTRUE 1.39 (.93,2.1) .33 .21 0.1121 > .10
study_name_f(TILDA):femaleTRUE 1.13 (.78,1.64) .12 .19 0.5270 > .10
study_name_f(LBLS):singleTRUE 1.4 (.74,2.66) .34 .32 0.2956 > .10
study_name_f(SATSA):singleTRUE 1.27 (.82,1.98) .24 .23 0.2921 > .10
. study_name_f(SHARE):singleTRUE .68 (.44,1.05) -.39 .22 0.0803 <=.10
. study_name_f(TILDA):singleTRUE 1.4 (.98,2.02) .34 .18 0.0674 <=.10
study_name_f(LBLS):poor_healthTRUE .7 (.36,1.34) -.35 .33 0.2852 > .10
study_name_f(SATSA):poor_healthTRUE 1.02 (.63,1.64) .02 .24 0.9382 > .10
study_name_f(SHARE):poor_healthTRUE .72 (.48,1.08) -.33 .21 0.1078 > .10
study_name_f(TILDA):poor_healthTRUE 1.19 (.8,1.77) .17 .2 0.3919 > .10
** study_name_f(LBLS):sedentaryTRUE 2.82 (1.39,5.64) 1.04 .36 0.0037 <=.01
study_name_f(SATSA):sedentaryTRUE 1.37 (.9,2.08) .31 .21 0.1402 > .10
study_name_f(SHARE):sedentaryTRUE 1.08 (.72,1.6) .08 .2 0.7107 > .10
study_name_f(TILDA):sedentaryTRUE 1.34 (.94,1.9) .29 .18 0.1021 > .10
study_name_f(LBLS):current_work_2TRUE .56 (.18,1.88) -.58 .59 0.3254 > .10
. study_name_f(SATSA):current_work_2TRUE .39 (.15,1.15) -.95 .52 0.0658 <=.10
study_name_f(SHARE):current_work_2TRUE .53 (.22,1.51) -.63 .49 0.1961 > .10
* study_name_f(TILDA):current_work_2TRUE .33 (.13,.92) -1.11 .48 0.0211 <=.05
* study_name_f(LBLS):current_drinkTRUE .44 (.23,.85) -.82 .33 0.0135 <=.05
*** study_name_f(SATSA):current_drinkTRUE 2.59 (1.55,4.35) .95 .26 0.0003 <=.001
study_name_f(SHARE):current_drinkTRUE 1.12 (.75,1.67) .11 .21 0.5790 > .10
study_name_f(TILDA):current_drinkTRUE 1.19 (.8,1.77) .18 .2 0.3901 > .10
. educ3_f( < HS ):poor_healthTRUE 1.29 (.98,1.69) .25 .14 0.0654 <=.10
educ3_f( HS < ):poor_healthTRUE .87 (.59,1.26) -.14 .19 0.4600 > .10
educ3_f( < HS ):current_work_2TRUE .89 (.68,1.15) -.12 .13 0.3639 > .10
* educ3_f( HS < ):current_work_2TRUE .63 (.42,.94) -.46 .21 0.0239 <=.05
. educ3_f( < HS ):current_drinkTRUE .77 (.59,1.02) -.26 .14 0.0680 <=.10
educ3_f( HS < ):current_drinkTRUE 1.23 (.85,1.79) .21 .19 0.2805 > .10

alsa

BETWEEN

coef_name A B AA BB best
(Intercept) .19(.14,.26)*** .14(.09,.21)*** .15(.09,.24)*** .18(.07,.42)*** .14(.13,.15)***
age_in_years_70 .95(.93,.97)*** .95(.93,.97)*** .98(.93,1.03) .94(.87,1.01) .98(.97,.99)***
femaleTRUE .57(.42,.76)*** .6(.44,.81)*** .96(.53,1.71) .65(.28,1.56)
educ3_f( < HS ) 1.23(.81,1.84) 1.22(.8,1.82) 1.43(.64,3.1) 1.44(.41,4.83)
educ3_f( HS < ) 1.06(.77,1.45) 1.05(.76,1.44) 1.16(.64,2.11) 1.01(.42,2.43)
singleTRUE 1.28(.92,1.77) 1.3(.93,1.79) 1.02(.45,2.19) .69(.23,1.91) 1.39(1.13,1.69)**
poor_healthTRUE 1.12(.82,1.53) 1.17(.48,2.83)
sedentaryTRUE 1.16(.85,1.56) .96(.38,2.35)
current_work_2TRUE 1.75(.64,4.1) 61.72(.52,19638.03)
current_drinkTRUE 1.38(1.01,1.92)* .7(.31,1.64)
age_in_years_70:femaleTRUE .92(.87,.98)** .92(.87,.98)** .99(.99,1).
age_in_years_70:educ3_f( < HS ) 1.02(.95,1.1) 1(.93,1.08)
age_in_years_70:educ3_f( HS < ) .98(.93,1.04) .98(.92,1.04)
age_in_years_70:singleTRUE 1(.95,1.05) 1.01(.95,1.07)
age_in_years_70:poor_healthTRUE 1(.94,1.06)
age_in_years_70:sedentaryTRUE 1.01(.96,1.07)
age_in_years_70:current_work_2TRUE .75(.47,1.02)
age_in_years_70:current_drinkTRUE 1.05(.99,1.12). .98(.98,.99)***
femaleTRUE:educ3_f( < HS ) .45(.16,1.18) .31(.1,.89)*
femaleTRUE:educ3_f( HS < ) .78(.39,1.53) .72(.35,1.47)
femaleTRUE:singleTRUE 1.7(.84,3.54) 2.1(1,4.55).
femaleTRUE:poor_healthTRUE 1.36(.66,2.79)
femaleTRUE:sedentaryTRUE 1.35(.67,2.76)
femaleTRUE:current_work_2TRUE .14(0,4)
femaleTRUE:current_drinkTRUE 1.39(.66,2.92)
educ3_f( < HS ):singleTRUE .74(.28,1.93) .88(.32,2.41)
educ3_f( HS < ):singleTRUE 1.37(.67,2.84) 1.33(.63,2.86)
educ3_f( < HS ):poor_healthTRUE .99(.4,2.46)
educ3_f( HS < ):poor_healthTRUE .77(.37,1.57)
educ3_f( < HS ):sedentaryTRUE 2.71(1.11,6.82)*
educ3_f( HS < ):sedentaryTRUE 1.1(.54,2.24)
educ3_f( < HS ):current_work_2TRUE 1.09(.03,37.99)
educ3_f( HS < ):current_work_2TRUE .46(.02,6.09)
educ3_f( < HS ):current_drinkTRUE .67(.26,1.75)
educ3_f( HS < ):current_drinkTRUE 1.38(.65,2.93)
singleTRUE:poor_healthTRUE 1.1(.53,2.28)
singleTRUE:sedentaryTRUE .63(.3,1.28)
singleTRUE:current_work_2TRUE 2.3(.17,38.18)
singleTRUE:current_drinkTRUE 1.63(.76,3.59) 1.52(1.26,1.83)***
poor_healthTRUE:sedentaryTRUE .72(.37,1.42)
poor_healthTRUE:current_work_2TRUE 8.41(.69,204.5)
poor_healthTRUE:current_drinkTRUE 1.01(.5,2.07)
sedentaryTRUE:current_work_2TRUE 3.27(.31,51.92)
sedentaryTRUE:current_drinkTRUE 1.02(.51,2.05)
current_work_2TRUE:current_drinkTRUE .02(0,.81).

A

solution of model A fit to data from alsa study

logLik dev AIC BIC df_Null df_Model df_drop
-672.2898 1344.58 1356.6 1390.3 2052 2047 5
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .19 (.14,.26) -1.65 .16 0.0000 <=.001
*** age_in_years_70 .95 (.93,.97) -.05 .01 0.0000 <=.001
*** femaleTRUE .57 (.42,.76) -.57 .15 0.0002 <=.001
educ3_f( < HS ) 1.23 (.81,1.84) .21 .21 0.3191 > .10
educ3_f( HS < ) 1.06 (.77,1.45) .06 .16 0.7215 > .10
singleTRUE 1.28 (.92,1.77) .25 .17 0.1327 > .10

B

solution of model B fit to data from alsa study

logLik dev AIC BIC df_Null df_Model df_drop
-669.032 1338.064 1358.1 1414.3 2052 2043 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .14 (.09,.21) -2 .22 0.0000 <=.001
*** age_in_years_70 .95 (.93,.97) -.05 .01 0.0001 <=.001
*** femaleTRUE .6 (.44,.81) -.51 .16 0.0009 <=.001
educ3_f( < HS ) 1.22 (.8,1.82) .2 .21 0.3455 > .10
educ3_f( HS < ) 1.05 (.76,1.44) .05 .16 0.7644 > .10
singleTRUE 1.3 (.93,1.79) .26 .17 0.1201 > .10
poor_healthTRUE 1.12 (.82,1.53) .12 .16 0.4687 > .10
sedentaryTRUE 1.16 (.85,1.56) .15 .15 0.3424 > .10
current_work_2TRUE 1.75 (.64,4.1) .56 .47 0.2300 > .10
* current_drinkTRUE 1.38 (1.01,1.92) .33 .16 0.0487 <=.05

AA

solution of model AA fit to data from alsa study

logLik dev AIC BIC df_Null df_Model df_drop
-664.002 1328.004 1358 1442.4 2052 2038 14
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .15 (.09,.24) -1.9 .24 0.0000 <=.001
age_in_years_70 .98 (.93,1.03) -.02 .03 0.3972 > .10
femaleTRUE .96 (.53,1.71) -.04 .3 0.8809 > .10
educ3_f( < HS ) 1.43 (.64,3.1) .36 .4 0.3695 > .10
educ3_f( HS < ) 1.16 (.64,2.11) .15 .3 0.6276 > .10
singleTRUE 1.02 (.45,2.19) .02 .4 0.9673 > .10
** age_in_years_70:femaleTRUE .92 (.87,.98) -.08 .03 0.0046 <=.01
age_in_years_70:educ3_f( < HS ) 1.02 (.95,1.1) .02 .04 0.5310 > .10
age_in_years_70:educ3_f( HS < ) .98 (.93,1.04) -.02 .03 0.5682 > .10
age_in_years_70:singleTRUE 1 (.95,1.05) 0 .03 0.9437 > .10
femaleTRUE:educ3_f( < HS ) .45 (.16,1.18) -.8 .5 0.1141 > .10
femaleTRUE:educ3_f( HS < ) .78 (.39,1.53) -.25 .35 0.4639 > .10
femaleTRUE:singleTRUE 1.7 (.84,3.54) .53 .37 0.1477 > .10
educ3_f( < HS ):singleTRUE .74 (.28,1.93) -.3 .49 0.5408 > .10
educ3_f( HS < ):singleTRUE 1.37 (.67,2.84) .31 .37 0.3950 > .10

BB

solution of model BB fit to data from alsa study

logLik dev AIC BIC df_Null df_Model df_drop
-647.6469 1295.294 1385.3 1638.5 2052 2008 44
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .18 (.07,.42) -1.69 .44 0.0001 <=.001
age_in_years_70 .94 (.87,1.01) -.06 .04 0.1157 > .10
femaleTRUE .65 (.28,1.56) -.43 .44 0.3311 > .10
educ3_f( < HS ) 1.44 (.41,4.83) .36 .63 0.5615 > .10
educ3_f( HS < ) 1.01 (.42,2.43) .01 .45 0.9771 > .10
singleTRUE .69 (.23,1.91) -.37 .54 0.4889 > .10
poor_healthTRUE 1.17 (.48,2.83) .16 .45 0.7236 > .10
sedentaryTRUE .96 (.38,2.35) -.04 .46 0.9378 > .10
current_work_2TRUE 61.72 (.52,19638.03) 4.12 2.53 0.1036 > .10
current_drinkTRUE .7 (.31,1.64) -.35 .42 0.4003 > .10
** age_in_years_70:femaleTRUE .92 (.87,.98) -.08 .03 0.0055 <=.01
age_in_years_70:educ3_f( < HS ) 1 (.93,1.08) 0 .04 0.9132 > .10
age_in_years_70:educ3_f( HS < ) .98 (.92,1.04) -.02 .03 0.5117 > .10
age_in_years_70:singleTRUE 1.01 (.95,1.07) .01 .03 0.7665 > .10
age_in_years_70:poor_healthTRUE 1 (.94,1.06) 0 .03 0.9920 > .10
age_in_years_70:sedentaryTRUE 1.01 (.96,1.07) .01 .03 0.6563 > .10
age_in_years_70:current_work_2TRUE .75 (.47,1.02) -.28 .19 0.1321 > .10
. age_in_years_70:current_drinkTRUE 1.05 (.99,1.12) .05 .03 0.0968 <=.10
* femaleTRUE:educ3_f( < HS ) .31 (.1,.89) -1.17 .55 0.0339 <=.05
femaleTRUE:educ3_f( HS < ) .72 (.35,1.47) -.33 .36 0.3642 > .10
. femaleTRUE:singleTRUE 2.1 (1,4.55) .74 .39 0.0543 <=.10
femaleTRUE:poor_healthTRUE 1.36 (.66,2.79) .31 .37 0.3975 > .10
femaleTRUE:sedentaryTRUE 1.35 (.67,2.76) .3 .36 0.4040 > .10
femaleTRUE:current_work_2TRUE .14 (0,4) -1.98 1.95 0.3098 > .10
femaleTRUE:current_drinkTRUE 1.39 (.66,2.92) .33 .38 0.3824 > .10
educ3_f( < HS ):singleTRUE .88 (.32,2.41) -.13 .52 0.8080 > .10
educ3_f( HS < ):singleTRUE 1.33 (.63,2.86) .29 .39 0.4551 > .10
educ3_f( < HS ):poor_healthTRUE .99 (.4,2.46) -.01 .46 0.9886 > .10
educ3_f( HS < ):poor_healthTRUE .77 (.37,1.57) -.26 .36 0.4770 > .10
* educ3_f( < HS ):sedentaryTRUE 2.71 (1.11,6.82) 1 .46 0.0304 <=.05
educ3_f( HS < ):sedentaryTRUE 1.1 (.54,2.24) .1 .36 0.7884 > .10
educ3_f( < HS ):current_work_2TRUE 1.09 (.03,37.99) .09 1.67 0.9584 > .10
educ3_f( HS < ):current_work_2TRUE .46 (.02,6.09) -.77 1.38 0.5762 > .10
educ3_f( < HS ):current_drinkTRUE .67 (.26,1.75) -.4 .49 0.4083 > .10
educ3_f( HS < ):current_drinkTRUE 1.38 (.65,2.93) .32 .38 0.4004 > .10
singleTRUE:poor_healthTRUE 1.1 (.53,2.28) .1 .37 0.7914 > .10
singleTRUE:sedentaryTRUE .63 (.3,1.28) -.47 .37 0.2051 > .10
singleTRUE:current_work_2TRUE 2.3 (.17,38.18) .83 1.32 0.5278 > .10
singleTRUE:current_drinkTRUE 1.63 (.76,3.59) .49 .4 0.2191 > .10
poor_healthTRUE:sedentaryTRUE .72 (.37,1.42) -.32 .34 0.3468 > .10
poor_healthTRUE:current_work_2TRUE 8.41 (.69,204.5) 2.13 1.38 0.1217 > .10
poor_healthTRUE:current_drinkTRUE 1.01 (.5,2.07) .01 .36 0.9782 > .10
sedentaryTRUE:current_work_2TRUE 3.27 (.31,51.92) 1.18 1.24 0.3392 > .10
sedentaryTRUE:current_drinkTRUE 1.02 (.51,2.05) .02 .35 0.9583 > .10
. current_work_2TRUE:current_drinkTRUE .02 (0,.81) -3.77 2.13 0.0768 <=.10

best

solution of model best fit to data from alsa study

logLik dev AIC BIC df_Null df_Model df_drop
-5349.962 10699.92 10713.9 10765.9 12327 12321 6
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .14 (.13,.15) -1.94 .04 0.0000 <=.001
*** age_in_years_70 .98 (.97,.99) -.02 0 0.0000 <=.001
** singleTRUE 1.39 (1.13,1.69) .33 .1 0.0014 <=.01
. age_in_years_70:femaleTRUE .99 (.99,1) -.01 0 0.0999 <=.10
*** singleTRUE:femaleTRUE .7 (.59,.84) -.35 .09 0.0001 <=.001
*** age_in_years_70:current_drinkTRUE .98 (.98,.99) -.02 0 0.0001 <=.001
*** singleTRUE:current_drinkTRUE 1.52 (1.26,1.83) .42 .09 0.0000 <=.001

lbsl

BETWEEN

coef_name A B AA BB best
(Intercept) .09(.05,.17)*** .11(.05,.22)*** .1(.04,.23)*** .05(.01,.28)** .14(.13,.15)***
age_in_years_70 .97(.95,.99)** .97(.94,.99)** .95(.9,1)* .9(.83,.98)* .98(.96,.99)***
femaleTRUE 1.45(.84,2.53) 1.35(.78,2.39) .86(.25,2.98) .31(.04,2.11)
educ3_f( < HS ) 1.58(.67,3.59) 1.62(.67,3.77) 1.45(.25,6.78) 5.35(.33,70.89)
educ3_f( HS < ) .84(.46,1.57) .95(.51,1.8) 1.02(.37,3.14) 2.01(.35,13.01)
singleTRUE 1.65(.97,2.81). 1.68(.97,2.9). 1.2(.27,4.83) 2.27(.29,17.5)
poor_healthTRUE .73(.42,1.27) .66(.11,3.76)
sedentaryTRUE 2.97(1.56,5.55)*** 10.07(1.43,71.57)* 1.6(1.43,1.77)***
current_work_2TRUE .9(.45,1.78) 1.53(.16,11.94)
current_drinkTRUE .64(.37,1.11) 1(.16,6.62)
age_in_years_70:femaleTRUE 1.03(.99,1.08) 1.02(.97,1.08) .99(.99,1)
age_in_years_70:educ3_f( < HS ) .98(.89,1.07) .92(.81,1.03)
age_in_years_70:educ3_f( HS < ) 1.03(.99,1.08) 1.01(.95,1.07)
age_in_years_70:singleTRUE .97(.93,1.01) .97(.92,1.03) .99(.98,1)
age_in_years_70:poor_healthTRUE 1.03(.97,1.09) .99(.98,1)*
age_in_years_70:sedentaryTRUE 1.04(.97,1.12)
age_in_years_70:current_work_2TRUE 1.05(.99,1.11). 1.02(1.01,1.03)***
age_in_years_70:current_drinkTRUE 1.04(.98,1.1) .98(.97,.99)***
femaleTRUE:educ3_f( < HS ) 2.06(.28,16.57) 1.17(.1,14.18)
femaleTRUE:educ3_f( HS < ) 1.71(.43,6.72) 1.89(.37,10.14)
femaleTRUE:singleTRUE 2.37(.71,8.72) 5.13(1.23,25.99)* .82(.71,.95)*
femaleTRUE:poor_healthTRUE 1.73(.43,7.25)
femaleTRUE:sedentaryTRUE .98(.18,5.75)
femaleTRUE:current_work_2TRUE .81(.17,3.82)
femaleTRUE:current_drinkTRUE 2.01(.44,9.83)
educ3_f( < HS ):singleTRUE .85(.11,6.93) 3.16(.23,49.8)
educ3_f( HS < ):singleTRUE .49(.13,1.83) .46(.08,2.41)
educ3_f( < HS ):poor_healthTRUE .81(.1,6.52)
educ3_f( HS < ):poor_healthTRUE .96(.23,4.04)
educ3_f( < HS ):sedentaryTRUE .89(.09,10.33)
educ3_f( HS < ):sedentaryTRUE .33(.06,1.78)
educ3_f( < HS ):current_work_2TRUE .12(0,2.21)
educ3_f( HS < ):current_work_2TRUE .3(.05,1.56)
educ3_f( < HS ):current_drinkTRUE .28(.03,2.56)
educ3_f( HS < ):current_drinkTRUE 1.1(.23,5.45)
singleTRUE:poor_healthTRUE .52(.13,2.15)
singleTRUE:sedentaryTRUE .64(.12,3.32)
singleTRUE:current_work_2TRUE 1.78(.35,9.33)
singleTRUE:current_drinkTRUE .26(.05,1.12). 1.84(1.59,2.13)***
poor_healthTRUE:sedentaryTRUE 1.33(.3,6.14)
poor_healthTRUE:current_work_2TRUE .85(.16,4.09)
poor_healthTRUE:current_drinkTRUE 1.82(.47,7.41)
sedentaryTRUE:current_work_2TRUE 6.53(.89,55.81).
sedentaryTRUE:current_drinkTRUE .25(.04,1.24)
current_work_2TRUE:current_drinkTRUE 1.94(.39,11.33)

A

solution of model A fit to data from lbsl study

logLik dev AIC BIC df_Null df_Model df_drop
-195.815 391.63 403.6 429.2 522 517 5
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .09 (.05,.17) -2.39 .32 0.0000 <=.001
** age_in_years_70 .97 (.95,.99) -.03 .01 0.0038 <=.01
femaleTRUE 1.45 (.84,2.53) .37 .28 0.1873 > .10
educ3_f( < HS ) 1.58 (.67,3.59) .46 .42 0.2823 > .10
educ3_f( HS < ) .84 (.46,1.57) -.17 .31 0.5807 > .10
. singleTRUE 1.65 (.97,2.81) .5 .27 0.0668 <=.10

B

solution of model B fit to data from lbsl study

logLik dev AIC BIC df_Null df_Model df_drop
-188.4152 376.8303 396.8 439.4 522 513 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .11 (.05,.22) -2.22 .38 0.0000 <=.001
** age_in_years_70 .97 (.94,.99) -.03 .01 0.0052 <=.01
femaleTRUE 1.35 (.78,2.39) .3 .29 0.2908 > .10
educ3_f( < HS ) 1.62 (.67,3.77) .48 .44 0.2667 > .10
educ3_f( HS < ) .95 (.51,1.8) -.05 .32 0.8646 > .10
. singleTRUE 1.68 (.97,2.9) .52 .28 0.0621 <=.10
poor_healthTRUE .73 (.42,1.27) -.31 .28 0.2740 > .10
*** sedentaryTRUE 2.97 (1.56,5.55) 1.09 .32 0.0007 <=.001
current_work_2TRUE .9 (.45,1.78) -.1 .35 0.7647 > .10
current_drinkTRUE .64 (.37,1.11) -.45 .28 0.1108 > .10

AA

solution of model AA fit to data from lbsl study

logLik dev AIC BIC df_Null df_Model df_drop
-190.5223 381.0446 411 474.9 522 508 14
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .1 (.04,.23) -2.29 .46 0.0000 <=.001
* age_in_years_70 .95 (.9,1) -.05 .03 0.0383 <=.05
femaleTRUE .86 (.25,2.98) -.15 .62 0.8135 > .10
educ3_f( < HS ) 1.45 (.25,6.78) .37 .82 0.6502 > .10
educ3_f( HS < ) 1.02 (.37,3.14) .02 .54 0.9733 > .10
singleTRUE 1.2 (.27,4.83) .18 .73 0.8008 > .10
age_in_years_70:femaleTRUE 1.03 (.99,1.08) .03 .02 0.1418 > .10
age_in_years_70:educ3_f( < HS ) .98 (.89,1.07) -.02 .05 0.6083 > .10
age_in_years_70:educ3_f( HS < ) 1.03 (.99,1.08) .03 .02 0.1543 > .10
age_in_years_70:singleTRUE .97 (.93,1.01) -.03 .02 0.1590 > .10
femaleTRUE:educ3_f( < HS ) 2.06 (.28,16.57) .72 1.02 0.4820 > .10
femaleTRUE:educ3_f( HS < ) 1.71 (.43,6.72) .54 .69 0.4388 > .10
femaleTRUE:singleTRUE 2.37 (.71,8.72) .86 .63 0.1731 > .10
educ3_f( < HS ):singleTRUE .85 (.11,6.93) -.17 1.05 0.8732 > .10
educ3_f( HS < ):singleTRUE .49 (.13,1.83) -.7 .67 0.2953 > .10

BB

solution of model BB fit to data from lbsl study

logLik dev AIC BIC df_Null df_Model df_drop
-171.3046 342.6091 432.6 624.3 522 478 44
sign coef_name odds odds_ci est se p sign_
** (Intercept) .05 (.01,.28) -2.96 .94 0.0017 <=.01
* age_in_years_70 .9 (.83,.98) -.1 .04 0.0165 <=.05
femaleTRUE .31 (.04,2.11) -1.17 1 0.2404 > .10
educ3_f( < HS ) 5.35 (.33,70.89) 1.68 1.34 0.2115 > .10
educ3_f( HS < ) 2.01 (.35,13.01) .7 .91 0.4446 > .10
singleTRUE 2.27 (.29,17.5) .82 1.04 0.4310 > .10
poor_healthTRUE .66 (.11,3.76) -.41 .89 0.6446 > .10
* sedentaryTRUE 10.07 (1.43,71.57) 2.31 .99 0.0192 <=.05
current_work_2TRUE 1.53 (.16,11.94) .43 1.08 0.6926 > .10
current_drinkTRUE 1 (.16,6.62) 0 .94 0.9984 > .10
age_in_years_70:femaleTRUE 1.02 (.97,1.08) .02 .03 0.4195 > .10
age_in_years_70:educ3_f( < HS ) .92 (.81,1.03) -.09 .06 0.1511 > .10
age_in_years_70:educ3_f( HS < ) 1.01 (.95,1.07) .01 .03 0.7474 > .10
age_in_years_70:singleTRUE .97 (.92,1.03) -.03 .03 0.2938 > .10
age_in_years_70:poor_healthTRUE 1.03 (.97,1.09) .03 .03 0.4032 > .10
age_in_years_70:sedentaryTRUE 1.04 (.97,1.12) .04 .04 0.2757 > .10
. age_in_years_70:current_work_2TRUE 1.05 (.99,1.11) .05 .03 0.0909 <=.10
age_in_years_70:current_drinkTRUE 1.04 (.98,1.1) .04 .03 0.1938 > .10
femaleTRUE:educ3_f( < HS ) 1.17 (.1,14.18) .16 1.25 0.8983 > .10
femaleTRUE:educ3_f( HS < ) 1.89 (.37,10.14) .64 .83 0.4450 > .10
* femaleTRUE:singleTRUE 5.13 (1.23,25.99) 1.63 .77 0.0332 <=.05
femaleTRUE:poor_healthTRUE 1.73 (.43,7.25) .55 .72 0.4437 > .10
femaleTRUE:sedentaryTRUE .98 (.18,5.75) -.02 .87 0.9813 > .10
femaleTRUE:current_work_2TRUE .81 (.17,3.82) -.21 .79 0.7878 > .10
femaleTRUE:current_drinkTRUE 2.01 (.44,9.83) .7 .78 0.3717 > .10
educ3_f( < HS ):singleTRUE 3.16 (.23,49.8) 1.15 1.35 0.3926 > .10
educ3_f( HS < ):singleTRUE .46 (.08,2.41) -.77 .85 0.3631 > .10
educ3_f( < HS ):poor_healthTRUE .81 (.1,6.52) -.21 1.05 0.8411 > .10
educ3_f( HS < ):poor_healthTRUE .96 (.23,4.04) -.04 .73 0.9584 > .10
educ3_f( < HS ):sedentaryTRUE .89 (.09,10.33) -.12 1.2 0.9222 > .10
educ3_f( HS < ):sedentaryTRUE .33 (.06,1.78) -1.11 .87 0.2020 > .10
educ3_f( < HS ):current_work_2TRUE .12 (0,2.21) -2.09 1.55 0.1778 > .10
educ3_f( HS < ):current_work_2TRUE .3 (.05,1.56) -1.22 .85 0.1531 > .10
educ3_f( < HS ):current_drinkTRUE .28 (.03,2.56) -1.29 1.14 0.2578 > .10
educ3_f( HS < ):current_drinkTRUE 1.1 (.23,5.45) .1 .8 0.9024 > .10
singleTRUE:poor_healthTRUE .52 (.13,2.15) -.64 .72 0.3689 > .10
singleTRUE:sedentaryTRUE .64 (.12,3.32) -.44 .84 0.5982 > .10
singleTRUE:current_work_2TRUE 1.78 (.35,9.33) .57 .83 0.4892 > .10
. singleTRUE:current_drinkTRUE .26 (.05,1.12) -1.35 .77 0.0793 <=.10
poor_healthTRUE:sedentaryTRUE 1.33 (.3,6.14) .29 .76 0.7089 > .10
poor_healthTRUE:current_work_2TRUE .85 (.16,4.09) -.17 .82 0.8383 > .10
poor_healthTRUE:current_drinkTRUE 1.82 (.47,7.41) .6 .7 0.3917 > .10
. sedentaryTRUE:current_work_2TRUE 6.53 (.89,55.81) 1.88 1.04 0.0724 <=.10
sedentaryTRUE:current_drinkTRUE .25 (.04,1.24) -1.38 .84 0.1020 > .10
current_work_2TRUE:current_drinkTRUE 1.94 (.39,11.33) .66 .85 0.4373 > .10

best

solution of model best fit to data from lbsl study

logLik dev AIC BIC df_Null df_Model df_drop
-5303.738 10607.48 10627.5 10701.7 12327 12318 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .14 (.13,.15) -1.99 .04 0.0000 <=.001
*** age_in_years_70 .98 (.96,.99) -.03 .01 0.0000 <=.001
*** sedentaryTRUE 1.6 (1.43,1.77) .47 .05 0.0000 <=.001
age_in_years_70:femaleTRUE .99 (.99,1) -.01 0 0.1992 > .10
age_in_years_70:singleTRUE .99 (.98,1) -.01 0 0.1566 > .10
* femaleTRUE:singleTRUE .82 (.71,.95) -.2 .08 0.0103 <=.05
* age_in_years_70:poor_healthTRUE .99 (.98,1) -.01 0 0.0321 <=.05
*** age_in_years_70:current_work_2TRUE 1.02 (1.01,1.03) .02 0 0.0000 <=.001
*** age_in_years_70:current_drinkTRUE .98 (.97,.99) -.02 0 0.0000 <=.001
*** singleTRUE:current_drinkTRUE 1.84 (1.59,2.13) .61 .08 0.0000 <=.001

satsa

BETWEEN

coef_name A B AA BB best
(Intercept) .25(.15,.42)*** .08(.04,.15)*** .13(.04,.34)*** .03(0,.25)** .13(.11,.15)***
age_in_years_70 .95(.94,.96)*** .95(.93,.96)*** .93(.87,.98)* .76(.64,.87)*** .96(.95,.97)***
femaleTRUE .44(.34,.57)*** .48(.37,.63)*** .66(.22,1.98) .7(.15,3.2) .74(.66,.84)***
educ3_f( < HS ) 1.17(.72,1.98) 1.27(.77,2.17) 2.93(1.13,9.05)* 4.14(.47,73.97)
educ3_f( HS < ) 1.03(.51,2.06) 1.13(.56,2.28) 1.39(.36,5.56) 3.51(.24,85.22)
singleTRUE 1.46(1.09,1.94)* 1.59(1.18,2.13)** 2.17(.66,7.31) 4.75(.97,24.56). 1.6(1.4,1.84)***
poor_healthTRUE 1.19(.9,1.57) 1.68(.34,7.77) 1.39(1.22,1.58)***
sedentaryTRUE 1.58(1.19,2.12)** .64(.14,3.08)
current_work_2TRUE .67(.46,.97)* .01(0,.1)*** .64(.5,.8)***
current_drinkTRUE 2.87(2.03,4.12)*** 9.1(1.32,119.98)* 1.25(1.12,1.4)***
age_in_years_70:femaleTRUE .96(.93,.98)*** .98(.95,1.02)
age_in_years_70:educ3_f( < HS ) 1.05(.99,1.12) 1.23(1.1,1.45)** .99(.98,1.01)
age_in_years_70:educ3_f( HS < ) 1.02(.95,1.11) 1.15(1,1.37). 1.01(.99,1.03)
age_in_years_70:singleTRUE 1(.98,1.02) 1.01(.98,1.05)
age_in_years_70:poor_healthTRUE 1(.97,1.03)
age_in_years_70:sedentaryTRUE 1(.96,1.03) .99(.98,1)**
age_in_years_70:current_work_2TRUE .99(.96,1.03)
age_in_years_70:current_drinkTRUE 1.04(.99,1.08)
femaleTRUE:educ3_f( < HS ) .4(.13,1.19). .44(.12,1.62)
femaleTRUE:educ3_f( HS < ) .69(.16,2.95) .6(.11,3.15)
femaleTRUE:singleTRUE .76(.42,1.36) .78(.42,1.45)
femaleTRUE:poor_healthTRUE .73(.4,1.33)
femaleTRUE:sedentaryTRUE 1.1(.6,2.05)
femaleTRUE:current_work_2TRUE 2.04(.91,4.59). 1.36(1.1,1.67)**
femaleTRUE:current_drinkTRUE .99(.46,2.11)
educ3_f( < HS ):singleTRUE .8(.24,2.62) .81(.19,3.26)
educ3_f( HS < ):singleTRUE 1.17(.25,5.51) .89(.15,5.09)
educ3_f( < HS ):poor_healthTRUE 1.18(.32,4.77)
educ3_f( HS < ):poor_healthTRUE 1.29(.24,7.39)
educ3_f( < HS ):sedentaryTRUE 1.83(.49,6.57)
educ3_f( HS < ):sedentaryTRUE 2.03(.36,11.93)
educ3_f( < HS ):current_work_2TRUE 30.16(3.81,392.84)**
educ3_f( HS < ):current_work_2TRUE 10.75(.78,201.89).
educ3_f( < HS ):current_drinkTRUE .36(.03,2.06)
educ3_f( HS < ):current_drinkTRUE .22(.02,2.01)
singleTRUE:poor_healthTRUE .54(.28,1.02). .85(.68,1.06)
singleTRUE:sedentaryTRUE .66(.35,1.27)
singleTRUE:current_work_2TRUE 1.26(.5,3.16)
singleTRUE:current_drinkTRUE .8(.37,1.71)
poor_healthTRUE:sedentaryTRUE 1.09(.57,2.11)
poor_healthTRUE:current_work_2TRUE 1.38(.61,3.1)
poor_healthTRUE:current_drinkTRUE .62(.29,1.31)
sedentaryTRUE:current_work_2TRUE 1.25(.53,2.99)
sedentaryTRUE:current_drinkTRUE 1.43(.64,3.15)
current_work_2TRUE:current_drinkTRUE 1.56(.54,4.67)

A

solution of model A fit to data from satsa study

logLik dev AIC BIC df_Null df_Model df_drop
-688.693 1377.386 1389.4 1420.6 1351 1346 5
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .25 (.15,.42) -1.37 .26 0.0000 <=.001
*** age_in_years_70 .95 (.94,.96) -.06 .01 0.0000 <=.001
*** femaleTRUE .44 (.34,.57) -.83 .13 0.0000 <=.001
educ3_f( < HS ) 1.17 (.72,1.98) .16 .26 0.5407 > .10
educ3_f( HS < ) 1.03 (.51,2.06) .03 .35 0.9352 > .10
* singleTRUE 1.46 (1.09,1.94) .38 .15 0.0103 <=.05

B

solution of model B fit to data from satsa study

logLik dev AIC BIC df_Null df_Model df_drop
-663.8472 1327.694 1347.7 1399.8 1351 1342 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .08 (.04,.15) -2.5 .33 0.0000 <=.001
*** age_in_years_70 .95 (.93,.96) -.06 .01 0.0000 <=.001
*** femaleTRUE .48 (.37,.63) -.73 .14 0.0000 <=.001
educ3_f( < HS ) 1.27 (.77,2.17) .24 .26 0.3553 > .10
educ3_f( HS < ) 1.13 (.56,2.28) .12 .36 0.7405 > .10
** singleTRUE 1.59 (1.18,2.13) .46 .15 0.0023 <=.01
poor_healthTRUE 1.19 (.9,1.57) .17 .14 0.2304 > .10
** sedentaryTRUE 1.58 (1.19,2.12) .46 .15 0.0019 <=.01
* current_work_2TRUE .67 (.46,.97) -.4 .19 0.0369 <=.05
*** current_drinkTRUE 2.87 (2.03,4.12) 1.05 .18 0.0000 <=.001

AA

solution of model AA fit to data from satsa study

logLik dev AIC BIC df_Null df_Model df_drop
-675.0522 1350.104 1380.1 1458.2 1351 1337 14
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .13 (.04,.34) -2.02 .52 0.0001 <=.001
* age_in_years_70 .93 (.87,.98) -.08 .03 0.0131 <=.05
femaleTRUE .66 (.22,1.98) -.41 .55 0.4559 > .10
* educ3_f( < HS ) 2.93 (1.13,9.05) 1.08 .53 0.0409 <=.05
educ3_f( HS < ) 1.39 (.36,5.56) .33 .69 0.6362 > .10
singleTRUE 2.17 (.66,7.31) .78 .61 0.2020 > .10
*** age_in_years_70:femaleTRUE .96 (.93,.98) -.05 .01 0.0001 <=.001
age_in_years_70:educ3_f( < HS ) 1.05 (.99,1.12) .05 .03 0.1140 > .10
age_in_years_70:educ3_f( HS < ) 1.02 (.95,1.11) .02 .04 0.5602 > .10
age_in_years_70:singleTRUE 1 (.98,1.02) 0 .01 0.9965 > .10
. femaleTRUE:educ3_f( < HS ) .4 (.13,1.19) -.91 .55 0.0983 <=.10
femaleTRUE:educ3_f( HS < ) .69 (.16,2.95) -.37 .74 0.6180 > .10
femaleTRUE:singleTRUE .76 (.42,1.36) -.28 .3 0.3530 > .10
educ3_f( < HS ):singleTRUE .8 (.24,2.62) -.22 .6 0.7145 > .10
educ3_f( HS < ):singleTRUE 1.17 (.25,5.51) .16 .79 0.8376 > .10

BB

solution of model BB fit to data from satsa study

logLik dev AIC BIC df_Null df_Model df_drop
-635.8426 1271.685 1361.7 1596.1 1351 1307 44
sign coef_name odds odds_ci est se p sign_
** (Intercept) .03 (0,.25) -3.63 1.31 0.0057 <=.01
*** age_in_years_70 .76 (.64,.87) -.28 .07 0.0002 <=.001
femaleTRUE .7 (.15,3.2) -.36 .77 0.6411 > .10
educ3_f( < HS ) 4.14 (.47,73.97) 1.42 1.25 0.2572 > .10
educ3_f( HS < ) 3.51 (.24,85.22) 1.25 1.46 0.3910 > .10
. singleTRUE 4.75 (.97,24.56) 1.56 .82 0.0569 <=.10
poor_healthTRUE 1.68 (.34,7.77) .52 .79 0.5146 > .10
sedentaryTRUE .64 (.14,3.08) -.44 .78 0.5730 > .10
*** current_work_2TRUE .01 (0,.1) -4.72 1.34 0.0004 <=.001
* current_drinkTRUE 9.1 (1.32,119.98) 2.21 1.11 0.0473 <=.05
age_in_years_70:femaleTRUE .98 (.95,1.02) -.02 .02 0.3450 > .10
** age_in_years_70:educ3_f( < HS ) 1.23 (1.1,1.45) .21 .07 0.0027 <=.01
. age_in_years_70:educ3_f( HS < ) 1.15 (1,1.37) .14 .08 0.0720 <=.10
age_in_years_70:singleTRUE 1.01 (.98,1.05) .01 .02 0.4881 > .10
age_in_years_70:poor_healthTRUE 1 (.97,1.03) 0 .02 0.9173 > .10
age_in_years_70:sedentaryTRUE 1 (.96,1.03) 0 .02 0.9352 > .10
age_in_years_70:current_work_2TRUE .99 (.96,1.03) -.01 .02 0.6923 > .10
age_in_years_70:current_drinkTRUE 1.04 (.99,1.08) .03 .02 0.1220 > .10
femaleTRUE:educ3_f( < HS ) .44 (.12,1.62) -.82 .66 0.2104 > .10
femaleTRUE:educ3_f( HS < ) .6 (.11,3.15) -.5 .84 0.5495 > .10
femaleTRUE:singleTRUE .78 (.42,1.45) -.25 .32 0.4375 > .10
femaleTRUE:poor_healthTRUE .73 (.4,1.33) -.31 .3 0.3048 > .10
femaleTRUE:sedentaryTRUE 1.1 (.6,2.05) .1 .31 0.7555 > .10
. femaleTRUE:current_work_2TRUE 2.04 (.91,4.59) .71 .41 0.0836 <=.10
femaleTRUE:current_drinkTRUE .99 (.46,2.11) -.01 .39 0.9831 > .10
educ3_f( < HS ):singleTRUE .81 (.19,3.26) -.2 .71 0.7740 > .10
educ3_f( HS < ):singleTRUE .89 (.15,5.09) -.11 .89 0.9002 > .10
educ3_f( < HS ):poor_healthTRUE 1.18 (.32,4.77) .17 .68 0.8050 > .10
educ3_f( HS < ):poor_healthTRUE 1.29 (.24,7.39) .25 .87 0.7694 > .10
educ3_f( < HS ):sedentaryTRUE 1.83 (.49,6.57) .6 .66 0.3578 > .10
educ3_f( HS < ):sedentaryTRUE 2.03 (.36,11.93) .71 .89 0.4266 > .10
** educ3_f( < HS ):current_work_2TRUE 30.16 (3.81,392.84) 3.41 1.17 0.0035 <=.01
. educ3_f( HS < ):current_work_2TRUE 10.75 (.78,201.89) 2.38 1.4 0.0892 <=.10
educ3_f( < HS ):current_drinkTRUE .36 (.03,2.06) -1.02 1.02 0.3147 > .10
educ3_f( HS < ):current_drinkTRUE .22 (.02,2.01) -1.49 1.2 0.2118 > .10
. singleTRUE:poor_healthTRUE .54 (.28,1.02) -.62 .33 0.0570 <=.10
singleTRUE:sedentaryTRUE .66 (.35,1.27) -.41 .33 0.2170 > .10
singleTRUE:current_work_2TRUE 1.26 (.5,3.16) .24 .47 0.6142 > .10
singleTRUE:current_drinkTRUE .8 (.37,1.71) -.23 .39 0.5613 > .10
poor_healthTRUE:sedentaryTRUE 1.09 (.57,2.11) .09 .33 0.7878 > .10
poor_healthTRUE:current_work_2TRUE 1.38 (.61,3.1) .32 .41 0.4389 > .10
poor_healthTRUE:current_drinkTRUE .62 (.29,1.31) -.48 .39 0.2090 > .10
sedentaryTRUE:current_work_2TRUE 1.25 (.53,2.99) .22 .44 0.6182 > .10
sedentaryTRUE:current_drinkTRUE 1.43 (.64,3.15) .36 .41 0.3738 > .10
current_work_2TRUE:current_drinkTRUE 1.56 (.54,4.67) .45 .55 0.4145 > .10

best

solution of model best fit to data from satsa study

logLik dev AIC BIC df_Null df_Model df_drop
-5259.315 10518.63 10548.6 10659.9 12327 12313 14
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .13 (.11,.15) -2.04 .07 0.0000 <=.001
*** age_in_years_70 .96 (.95,.97) -.04 .01 0.0000 <=.001
*** femaleTRUE .74 (.66,.84) -.3 .06 0.0000 <=.001
*** singleTRUE 1.6 (1.4,1.84) .47 .07 0.0000 <=.001
*** poor_healthTRUE 1.39 (1.22,1.58) .33 .07 0.0000 <=.001
*** current_work_2TRUE .64 (.5,.8) -.45 .12 0.0002 <=.001
*** current_drinkTRUE 1.25 (1.12,1.4) .22 .06 0.0001 <=.001
singleTRUE:poor_healthTRUE .85 (.68,1.06) -.17 .11 0.1415 > .10
** age_in_years_70:sedentaryTRUE .99 (.98,1) -.01 0 0.0074 <=.01
** femaleTRUE:current_work_2TRUE 1.36 (1.1,1.67) .31 .11 0.0037 <=.01
*** current_drinkTRUE:sedentaryTRUE 1.54 (1.32,1.79) .43 .08 0.0000 <=.001
age_in_years_70:educ3_f( < HS ) .99 (.98,1.01) -.01 .01 0.3706 > .10
age_in_years_70:educ3_f( HS < ) 1.01 (.99,1.03) .01 .01 0.3018 > .10
current_work_2TRUE:educ3_f( < HS ) 1.01 (.78,1.3) .01 .13 0.9437 > .10
. current_work_2TRUE:educ3_f( HS < ) .72 (.5,1.02) -.33 .18 0.0661 <=.10

share

BETWEEN

coef_name A B AA BB best
(Intercept) .19(.15,.24)*** .18(.13,.24)*** .19(.13,.26)*** .23(.14,.39)*** .13(.11,.15)***
age_in_years_70 1(.99,1.01) 1(.99,1.01) .99(.97,1.02) .98(.95,1.02)
femaleTRUE 1.11(.89,1.39) 1.09(.87,1.37) 1.07(.7,1.65) .71(.4,1.26) .64(.56,.74)***
educ3_f( < HS ) 1(.78,1.29) 1.03(.8,1.32) 1.09(.71,1.67) .58(.32,1.07). 1.08(.94,1.24)
educ3_f( HS < ) .84(.64,1.11) .85(.64,1.12) .8(.5,1.29) .78(.4,1.52) .83(.69,1).
singleTRUE .86(.64,1.13) .85(.63,1.12) .74(.37,1.42) 1.24(.52,2.81)
poor_healthTRUE .88(.7,1.11) .86(.48,1.54) 1.31(1.04,1.65)*
sedentaryTRUE 1.23(.94,1.58) 1.02(.49,2.07)
current_work_2TRUE .94(.72,1.23) .82(.4,1.64) .63(.51,.77)***
current_drinkTRUE 1.45(1.15,1.83)** .75(.39,1.43)
age_in_years_70:femaleTRUE 1(.97,1.02) 1(.97,1.03)
age_in_years_70:educ3_f( < HS ) 1.02(.99,1.04) 1(.97,1.03)
age_in_years_70:educ3_f( HS < ) 1.01(.98,1.04) 1(.96,1.04)
age_in_years_70:singleTRUE 1(.97,1.03) 1(.97,1.03)
age_in_years_70:poor_healthTRUE 1.03(1,1.05).
age_in_years_70:sedentaryTRUE 1(.97,1.04)
age_in_years_70:current_work_2TRUE 1.01(.97,1.05)
age_in_years_70:current_drinkTRUE 1.01(.98,1.04) 1(.98,1.01)
femaleTRUE:educ3_f( < HS ) .93(.55,1.57) .91(.52,1.59)
femaleTRUE:educ3_f( HS < ) 1.24(.69,2.22) 1.22(.68,2.22)
femaleTRUE:singleTRUE .99(.54,1.89) .95(.5,1.84)
femaleTRUE:poor_healthTRUE 1.31(.79,2.21)
femaleTRUE:sedentaryTRUE 1.16(.66,2.04)
femaleTRUE:current_work_2TRUE 1.46(.81,2.62)
femaleTRUE:current_drinkTRUE 1.43(.87,2.36) 1.4(1.2,1.64)***
educ3_f( < HS ):singleTRUE 1.31(.68,2.57) 1.52(.75,3.12)
educ3_f( HS < ):singleTRUE 1.13(.52,2.42) 1.1(.49,2.44)
educ3_f( < HS ):poor_healthTRUE 2.14(1.22,3.79)** 1.37(1.08,1.74)*
educ3_f( HS < ):poor_healthTRUE 1.01(.52,1.95) .92(.65,1.29)
educ3_f( < HS ):sedentaryTRUE 2.11(1.1,4.09)*
educ3_f( HS < ):sedentaryTRUE 1.13(.54,2.31)
educ3_f( < HS ):current_work_2TRUE .76(.38,1.48)
educ3_f( HS < ):current_work_2TRUE .57(.28,1.14)
educ3_f( < HS ):current_drinkTRUE 1.24(.69,2.23)
educ3_f( HS < ):current_drinkTRUE 1.5(.82,2.74)
singleTRUE:poor_healthTRUE .47(.24,.91)*
singleTRUE:sedentaryTRUE .48(.2,1.05). 1.5(1.21,1.87)***
singleTRUE:current_work_2TRUE .75(.33,1.65)
singleTRUE:current_drinkTRUE 1.13(.61,2.07)
poor_healthTRUE:sedentaryTRUE .49(.27,.9)* .71(.57,.88)**
poor_healthTRUE:current_work_2TRUE .91(.49,1.66)
poor_healthTRUE:current_drinkTRUE 1.03(.6,1.78)
sedentaryTRUE:current_work_2TRUE 1.41(.74,2.72)
sedentaryTRUE:current_drinkTRUE 1.36(.7,2.6)
current_work_2TRUE:current_drinkTRUE 1.93(1.04,3.6)* 1.21(.95,1.56)

A

solution of model A fit to data from share study

logLik dev AIC BIC df_Null df_Model df_drop
-1115.067 2230.134 2242.1 2277.2 2554 2549 5
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .19 (.15,.24) -1.65 .12 0.0000 <=.001
age_in_years_70 1 (.99,1.01) 0 .01 0.8531 > .10
femaleTRUE 1.11 (.89,1.39) .1 .11 0.3571 > .10
educ3_f( < HS ) 1 (.78,1.29) 0 .13 0.9787 > .10
educ3_f( HS < ) .84 (.64,1.11) -.17 .14 0.2177 > .10
singleTRUE .86 (.64,1.13) -.16 .15 0.2816 > .10

B

solution of model B fit to data from share study

logLik dev AIC BIC df_Null df_Model df_drop
-1109.27 2218.539 2238.5 2297 2554 2545 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .18 (.13,.24) -1.73 .15 0.0000 <=.001
age_in_years_70 1 (.99,1.01) 0 .01 0.8845 > .10
femaleTRUE 1.09 (.87,1.37) .09 .12 0.4469 > .10
educ3_f( < HS ) 1.03 (.8,1.32) .03 .13 0.8397 > .10
educ3_f( HS < ) .85 (.64,1.12) -.17 .14 0.2371 > .10
singleTRUE .85 (.63,1.12) -.17 .15 0.2554 > .10
poor_healthTRUE .88 (.7,1.11) -.13 .12 0.2770 > .10
sedentaryTRUE 1.23 (.94,1.58) .21 .13 0.1200 > .10
current_work_2TRUE .94 (.72,1.23) -.06 .14 0.6660 > .10
** current_drinkTRUE 1.45 (1.15,1.83) .37 .12 0.0017 <=.01

AA

solution of model AA fit to data from share study

logLik dev AIC BIC df_Null df_Model df_drop
-1112.934 2225.869 2255.9 2343.6 2554 2540 14
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .19 (.13,.26) -1.67 .17 0.0000 <=.001
age_in_years_70 .99 (.97,1.02) -.01 .01 0.5547 > .10
femaleTRUE 1.07 (.7,1.65) .07 .22 0.7611 > .10
educ3_f( < HS ) 1.09 (.71,1.67) .08 .22 0.7024 > .10
educ3_f( HS < ) .8 (.5,1.29) -.22 .24 0.3626 > .10
singleTRUE .74 (.37,1.42) -.3 .34 0.3885 > .10
age_in_years_70:femaleTRUE 1 (.97,1.02) 0 .01 0.8562 > .10
age_in_years_70:educ3_f( < HS ) 1.02 (.99,1.04) .02 .01 0.2182 > .10
age_in_years_70:educ3_f( HS < ) 1.01 (.98,1.04) .01 .02 0.4082 > .10
age_in_years_70:singleTRUE 1 (.97,1.03) 0 .01 0.9320 > .10
femaleTRUE:educ3_f( < HS ) .93 (.55,1.57) -.07 .27 0.7840 > .10
femaleTRUE:educ3_f( HS < ) 1.24 (.69,2.22) .22 .3 0.4643 > .10
femaleTRUE:singleTRUE .99 (.54,1.89) -.01 .32 0.9814 > .10
educ3_f( < HS ):singleTRUE 1.31 (.68,2.57) .27 .34 0.4224 > .10
educ3_f( HS < ):singleTRUE 1.13 (.52,2.42) .12 .39 0.7612 > .10

BB

solution of model BB fit to data from share study

logLik dev AIC BIC df_Null df_Model df_drop
-1084.736 2169.472 2259.5 2522.5 2554 2510 44
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .23 (.14,.39) -1.45 .27 0.0000 <=.001
age_in_years_70 .98 (.95,1.02) -.02 .02 0.3026 > .10
femaleTRUE .71 (.4,1.26) -.34 .29 0.2437 > .10
. educ3_f( < HS ) .58 (.32,1.07) -.54 .31 0.0806 <=.10
educ3_f( HS < ) .78 (.4,1.52) -.24 .34 0.4731 > .10
singleTRUE 1.24 (.52,2.81) .21 .43 0.6213 > .10
poor_healthTRUE .86 (.48,1.54) -.15 .3 0.6107 > .10
sedentaryTRUE 1.02 (.49,2.07) .02 .37 0.9469 > .10
current_work_2TRUE .82 (.4,1.64) -.2 .36 0.5725 > .10
current_drinkTRUE .75 (.39,1.43) -.28 .33 0.3909 > .10
age_in_years_70:femaleTRUE 1 (.97,1.03) 0 .01 0.9366 > .10
age_in_years_70:educ3_f( < HS ) 1 (.97,1.03) 0 .02 0.8265 > .10
age_in_years_70:educ3_f( HS < ) 1 (.96,1.04) 0 .02 0.9352 > .10
age_in_years_70:singleTRUE 1 (.97,1.03) 0 .02 0.9585 > .10
. age_in_years_70:poor_healthTRUE 1.03 (1,1.05) .02 .01 0.0850 <=.10
age_in_years_70:sedentaryTRUE 1 (.97,1.04) 0 .02 0.8840 > .10
age_in_years_70:current_work_2TRUE 1.01 (.97,1.05) .01 .02 0.5474 > .10
age_in_years_70:current_drinkTRUE 1.01 (.98,1.04) .01 .02 0.3921 > .10
femaleTRUE:educ3_f( < HS ) .91 (.52,1.59) -.09 .29 0.7435 > .10
femaleTRUE:educ3_f( HS < ) 1.22 (.68,2.22) .2 .3 0.5041 > .10
femaleTRUE:singleTRUE .95 (.5,1.84) -.05 .33 0.8718 > .10
femaleTRUE:poor_healthTRUE 1.31 (.79,2.21) .27 .26 0.2996 > .10
femaleTRUE:sedentaryTRUE 1.16 (.66,2.04) .15 .29 0.6111 > .10
femaleTRUE:current_work_2TRUE 1.46 (.81,2.62) .38 .3 0.2016 > .10
femaleTRUE:current_drinkTRUE 1.43 (.87,2.36) .36 .26 0.1648 > .10
educ3_f( < HS ):singleTRUE 1.52 (.75,3.12) .42 .36 0.2490 > .10
educ3_f( HS < ):singleTRUE 1.1 (.49,2.44) .1 .41 0.8077 > .10
** educ3_f( < HS ):poor_healthTRUE 2.14 (1.22,3.79) .76 .29 0.0084 <=.01
educ3_f( HS < ):poor_healthTRUE 1.01 (.52,1.95) .01 .34 0.9766 > .10
* educ3_f( < HS ):sedentaryTRUE 2.11 (1.1,4.09) .75 .33 0.0257 <=.05
educ3_f( HS < ):sedentaryTRUE 1.13 (.54,2.31) .12 .37 0.7489 > .10
educ3_f( < HS ):current_work_2TRUE .76 (.38,1.48) -.28 .35 0.4234 > .10
educ3_f( HS < ):current_work_2TRUE .57 (.28,1.14) -.57 .36 0.1092 > .10
educ3_f( < HS ):current_drinkTRUE 1.24 (.69,2.23) .21 .3 0.4766 > .10
educ3_f( HS < ):current_drinkTRUE 1.5 (.82,2.74) .41 .31 0.1870 > .10
* singleTRUE:poor_healthTRUE .47 (.24,.91) -.75 .34 0.0251 <=.05
. singleTRUE:sedentaryTRUE .48 (.2,1.05) -.74 .42 0.0775 <=.10
singleTRUE:current_work_2TRUE .75 (.33,1.65) -.29 .41 0.4727 > .10
singleTRUE:current_drinkTRUE 1.13 (.61,2.07) .12 .31 0.7046 > .10
* poor_healthTRUE:sedentaryTRUE .49 (.27,.9) -.71 .31 0.0222 <=.05
poor_healthTRUE:current_work_2TRUE .91 (.49,1.66) -.09 .31 0.7627 > .10
poor_healthTRUE:current_drinkTRUE 1.03 (.6,1.78) .03 .28 0.9063 > .10
sedentaryTRUE:current_work_2TRUE 1.41 (.74,2.72) .35 .33 0.2988 > .10
sedentaryTRUE:current_drinkTRUE 1.36 (.7,2.6) .31 .33 0.3549 > .10
* current_work_2TRUE:current_drinkTRUE 1.93 (1.04,3.6) .66 .32 0.0371 <=.05

best

solution of model best fit to data from share study

logLik dev AIC BIC df_Null df_Model df_drop
-5259.089 10518.18 10554.2 10687.7 12327 12310 17
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .13 (.11,.15) -2.04 .07 0.0000 <=.001
educ3_f( < HS ) 1.08 (.94,1.24) .08 .07 0.2649 > .10
. educ3_f( HS < ) .83 (.69,1) -.18 .09 0.0500 <=.10
*** femaleTRUE .64 (.56,.74) -.44 .07 0.0000 <=.001
* poor_healthTRUE 1.31 (1.04,1.65) .27 .12 0.0227 <=.05
*** current_work_2TRUE .63 (.51,.77) -.47 .11 0.0000 <=.001
*** poor_healthFALSE:age_in_years_70 .96 (.95,.97) -.05 .01 0.0000 <=.001
*** poor_healthTRUE:age_in_years_70 .96 (.95,.97) -.04 .01 0.0000 <=.001
*** poor_healthFALSE:singleTRUE 1.69 (1.45,1.96) .52 .08 0.0000 <=.001
*** poor_healthTRUE:singleTRUE 1.41 (1.15,1.71) .34 .1 0.0007 <=.001
*** singleFALSE:sedentaryTRUE 1.83 (1.57,2.12) .6 .08 0.0000 <=.001
*** singleTRUE:sedentaryTRUE 1.5 (1.21,1.87) .41 .11 0.0002 <=.001
** poor_healthTRUE:sedentaryTRUE .71 (.57,.88) -.35 .11 0.0021 <=.01
age_in_years_70:current_drinkTRUE 1 (.98,1.01) 0 .01 0.4477 > .10
*** femaleTRUE:current_drinkTRUE 1.4 (1.2,1.64) .34 .08 0.0000 <=.001
current_work_2TRUE:current_drinkTRUE 1.21 (.95,1.56) .19 .13 0.1247 > .10
* educ3_f( < HS ):poor_healthTRUE 1.37 (1.08,1.74) .31 .12 0.0107 <=.05
educ3_f( HS < ):poor_healthTRUE .92 (.65,1.29) -.08 .17 0.6290 > .10

tilda

BETWEEN

coef_name A B AA BB best
(Intercept) .11(.09,.13)*** .08(.07,.11)*** .15(.11,.2)*** .07(.04,.12)*** .1(.08,.13)***
age_in_years_70 .95(.95,.96)*** .94(.93,.95)*** .97(.95,.99)** .97(.94,1).
femaleTRUE .93(.81,1.07) .91(.79,1.05) .65(.47,.9)* .78(.49,1.24) .74(.61,.89)**
educ3_f( < HS ) 1.27(1.09,1.47)** 1.18(1.01,1.38)* .88(.65,1.2) 1.26(.79,2.05)
educ3_f( HS < ) .39(.25,.58)*** .42(.27,.63)*** .47(.22,.91)* .16(.02,.75)*
singleTRUE 1.82(1.56,2.12)*** 1.8(1.54,2.1)*** 1.69(1.17,2.41)** 1.39(.83,2.31) 1.51(1.35,1.68)***
poor_healthTRUE 1.59(1.35,1.87)*** 1.85(1.07,3.18)* 1.35(1.19,1.53)***
sedentaryTRUE 1.54(1.29,1.83)*** 2.3(1.28,4.09)** 1.53(1.37,1.7)***
current_work_2TRUE .64(.54,.76)*** .88(.49,1.59) .77(.67,.9)***
current_drinkTRUE 1.36(1.16,1.61)*** 2.09(1.29,3.46)** 1.46(1.21,1.77)***
age_in_years_70:femaleTRUE .98(.96,1)* .98(.96,1)*
age_in_years_70:educ3_f( < HS ) .99(.97,1.01) .99(.97,1.01)
age_in_years_70:educ3_f( HS < ) 1.02(.97,1.07) 1.03(.97,1.09)
age_in_years_70:singleTRUE .99(.98,1.01) 1(.98,1.02)
age_in_years_70:poor_healthTRUE .98(.96,1)
age_in_years_70:sedentaryTRUE 1.01(.99,1.04)
age_in_years_70:current_work_2TRUE 1(.98,1.03)
age_in_years_70:current_drinkTRUE .99(.97,1.01)
femaleTRUE:educ3_f( < HS ) 1.49(1.1,2.03)* 1.3(.94,1.79) 1.17(.95,1.45)
femaleTRUE:educ3_f( HS < ) .94(.36,2.38) .95(.36,2.47) .85(.63,1.14)
femaleTRUE:singleTRUE .81(.59,1.1) .86(.62,1.19)
femaleTRUE:poor_healthTRUE 1.01(.71,1.43)
femaleTRUE:sedentaryTRUE .94(.65,1.36)
femaleTRUE:current_work_2TRUE 1.01(.71,1.44)
femaleTRUE:current_drinkTRUE .79(.55,1.12)
educ3_f( < HS ):singleTRUE 1.29(.92,1.82) 1.32(.93,1.89)
educ3_f( HS < ):singleTRUE 1.16(.46,2.81) 1.34(.51,3.38)
educ3_f( < HS ):poor_healthTRUE 1.06(.72,1.57)
educ3_f( HS < ):poor_healthTRUE 1.63(.45,5.1)
educ3_f( < HS ):sedentaryTRUE .84(.56,1.26)
educ3_f( HS < ):sedentaryTRUE 2.02(.67,5.72)
educ3_f( < HS ):current_work_2TRUE .88(.62,1.26)
educ3_f( HS < ):current_work_2TRUE 1.53(.54,4.48)
educ3_f( < HS ):current_drinkTRUE .64(.43,.95)*
educ3_f( HS < ):current_drinkTRUE 2.1(.51,14.64)
singleTRUE:poor_healthTRUE 1.03(.72,1.48)
singleTRUE:sedentaryTRUE 1.08(.72,1.61)
singleTRUE:current_work_2TRUE .98(.67,1.43)
singleTRUE:current_drinkTRUE 1.21(.84,1.76)
poor_healthTRUE:sedentaryTRUE .76(.51,1.12)
poor_healthTRUE:current_work_2TRUE .63(.41,.96)* .79(.6,1.04)
poor_healthTRUE:current_drinkTRUE .78(.54,1.14)
sedentaryTRUE:current_work_2TRUE .96(.61,1.48)
sedentaryTRUE:current_drinkTRUE .88(.59,1.32)
current_work_2TRUE:current_drinkTRUE .91(.6,1.41)

A

solution of model A fit to data from tilda study

logLik dev AIC BIC df_Null df_Model df_drop
-2588.705 5177.409 5189.4 5229.4 5844 5839 5
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .11 (.09,.13) -2.19 .09 0.0000 <=.001
*** age_in_years_70 .95 (.95,.96) -.05 0 0.0000 <=.001
femaleTRUE .93 (.81,1.07) -.07 .07 0.3197 > .10
** educ3_f( < HS ) 1.27 (1.09,1.47) .24 .08 0.0023 <=.01
*** educ3_f( HS < ) .39 (.25,.58) -.94 .21 0.0000 <=.001
*** singleTRUE 1.82 (1.56,2.12) .6 .08 0.0000 <=.001

B

solution of model B fit to data from tilda study

logLik dev AIC BIC df_Null df_Model df_drop
-2535.063 5070.126 5090.1 5156.9 5844 5835 9
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .08 (.07,.11) -2.48 .12 0.0000 <=.001
*** age_in_years_70 .94 (.93,.95) -.06 0 0.0000 <=.001
femaleTRUE .91 (.79,1.05) -.09 .07 0.2090 > .10
* educ3_f( < HS ) 1.18 (1.01,1.38) .16 .08 0.0362 <=.05
*** educ3_f( HS < ) .42 (.27,.63) -.86 .21 0.0000 <=.001
*** singleTRUE 1.8 (1.54,2.1) .59 .08 0.0000 <=.001
*** poor_healthTRUE 1.59 (1.35,1.87) .46 .08 0.0000 <=.001
*** sedentaryTRUE 1.54 (1.29,1.83) .43 .09 0.0000 <=.001
*** current_work_2TRUE .64 (.54,.76) -.44 .08 0.0000 <=.001
*** current_drinkTRUE 1.36 (1.16,1.61) .31 .08 0.0003 <=.001

AA

solution of model AA fit to data from tilda study

logLik dev AIC BIC df_Null df_Model df_drop
-2578.473 5156.947 5186.9 5287 5844 5830 14
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .15 (.11,.2) -1.89 .14 0.0000 <=.001
** age_in_years_70 .97 (.95,.99) -.03 .01 0.0015 <=.01
* femaleTRUE .65 (.47,.9) -.43 .17 0.0102 <=.05
educ3_f( < HS ) .88 (.65,1.2) -.13 .16 0.4142 > .10
* educ3_f( HS < ) .47 (.22,.91) -.76 .36 0.0344 <=.05
** singleTRUE 1.69 (1.17,2.41) .52 .18 0.0045 <=.01
* age_in_years_70:femaleTRUE .98 (.96,1) -.02 .01 0.0133 <=.05
age_in_years_70:educ3_f( < HS ) .99 (.97,1.01) -.01 .01 0.4150 > .10
age_in_years_70:educ3_f( HS < ) 1.02 (.97,1.07) .02 .03 0.3972 > .10
age_in_years_70:singleTRUE .99 (.98,1.01) -.01 .01 0.5054 > .10
* femaleTRUE:educ3_f( < HS ) 1.49 (1.1,2.03) .4 .16 0.0100 <=.05
femaleTRUE:educ3_f( HS < ) .94 (.36,2.38) -.06 .48 0.8950 > .10
femaleTRUE:singleTRUE .81 (.59,1.1) -.21 .16 0.1793 > .10
educ3_f( < HS ):singleTRUE 1.29 (.92,1.82) .25 .17 0.1442 > .10
educ3_f( HS < ):singleTRUE 1.16 (.46,2.81) .15 .46 0.7476 > .10

BB

solution of model BB fit to data from tilda study

logLik dev AIC BIC df_Null df_Model df_drop
-2512.134 5024.269 5114.3 5414.6 5844 5800 44
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .07 (.04,.12) -2.62 .27 0.0000 <=.001
. age_in_years_70 .97 (.94,1) -.03 .02 0.0917 <=.10
femaleTRUE .78 (.49,1.24) -.25 .24 0.2971 > .10
educ3_f( < HS ) 1.26 (.79,2.05) .23 .24 0.3410 > .10
* educ3_f( HS < ) .16 (.02,.75) -1.82 .88 0.0393 <=.05
singleTRUE 1.39 (.83,2.31) .33 .26 0.2045 > .10
* poor_healthTRUE 1.85 (1.07,3.18) .61 .28 0.0268 <=.05
** sedentaryTRUE 2.3 (1.28,4.09) .83 .3 0.0048 <=.01
current_work_2TRUE .88 (.49,1.59) -.12 .3 0.6828 > .10
** current_drinkTRUE 2.09 (1.29,3.46) .74 .25 0.0035 <=.01
* age_in_years_70:femaleTRUE .98 (.96,1) -.02 .01 0.0156 <=.05
age_in_years_70:educ3_f( < HS ) .99 (.97,1.01) -.01 .01 0.2212 > .10
age_in_years_70:educ3_f( HS < ) 1.03 (.97,1.09) .03 .03 0.3278 > .10
age_in_years_70:singleTRUE 1 (.98,1.02) 0 .01 0.8225 > .10
age_in_years_70:poor_healthTRUE .98 (.96,1) -.02 .01 0.1056 > .10
age_in_years_70:sedentaryTRUE 1.01 (.99,1.04) .01 .01 0.2551 > .10
age_in_years_70:current_work_2TRUE 1 (.98,1.03) 0 .01 0.7688 > .10
age_in_years_70:current_drinkTRUE .99 (.97,1.01) -.01 .01 0.2739 > .10
femaleTRUE:educ3_f( < HS ) 1.3 (.94,1.79) .26 .16 0.1142 > .10
femaleTRUE:educ3_f( HS < ) .95 (.36,2.47) -.05 .49 0.9189 > .10
femaleTRUE:singleTRUE .86 (.62,1.19) -.15 .16 0.3658 > .10
femaleTRUE:poor_healthTRUE 1.01 (.71,1.43) .01 .18 0.9472 > .10
femaleTRUE:sedentaryTRUE .94 (.65,1.36) -.06 .19 0.7424 > .10
femaleTRUE:current_work_2TRUE 1.01 (.71,1.44) .01 .18 0.9528 > .10
femaleTRUE:current_drinkTRUE .79 (.55,1.12) -.24 .18 0.1921 > .10
educ3_f( < HS ):singleTRUE 1.32 (.93,1.89) .28 .18 0.1226 > .10
educ3_f( HS < ):singleTRUE 1.34 (.51,3.38) .29 .48 0.5412 > .10
educ3_f( < HS ):poor_healthTRUE 1.06 (.72,1.57) .06 .2 0.7747 > .10
educ3_f( HS < ):poor_healthTRUE 1.63 (.45,5.1) .49 .61 0.4254 > .10
educ3_f( < HS ):sedentaryTRUE .84 (.56,1.26) -.17 .21 0.3957 > .10
educ3_f( HS < ):sedentaryTRUE 2.02 (.67,5.72) .71 .54 0.1928 > .10
educ3_f( < HS ):current_work_2TRUE .88 (.62,1.26) -.13 .18 0.4885 > .10
educ3_f( HS < ):current_work_2TRUE 1.53 (.54,4.48) .43 .54 0.4264 > .10
* educ3_f( < HS ):current_drinkTRUE .64 (.43,.95) -.45 .2 0.0273 <=.05
educ3_f( HS < ):current_drinkTRUE 2.1 (.51,14.64) .74 .82 0.3667 > .10
singleTRUE:poor_healthTRUE 1.03 (.72,1.48) .03 .18 0.8577 > .10
singleTRUE:sedentaryTRUE 1.08 (.72,1.61) .08 .21 0.7149 > .10
singleTRUE:current_work_2TRUE .98 (.67,1.43) -.02 .19 0.9173 > .10
singleTRUE:current_drinkTRUE 1.21 (.84,1.76) .19 .19 0.3114 > .10
poor_healthTRUE:sedentaryTRUE .76 (.51,1.12) -.28 .2 0.1601 > .10
* poor_healthTRUE:current_work_2TRUE .63 (.41,.96) -.46 .22 0.0325 <=.05
poor_healthTRUE:current_drinkTRUE .78 (.54,1.14) -.24 .19 0.2023 > .10
sedentaryTRUE:current_work_2TRUE .96 (.61,1.48) -.04 .22 0.8447 > .10
sedentaryTRUE:current_drinkTRUE .88 (.59,1.32) -.13 .21 0.5315 > .10
current_work_2TRUE:current_drinkTRUE .91 (.6,1.41) -.09 .22 0.6784 > .10

best

solution of model best fit to data from tilda study

logLik dev AIC BIC df_Null df_Model df_drop
-5254.911 10509.82 10543.8 10670 12327 12311 16
sign coef_name odds odds_ci est se p sign_
*** (Intercept) .1 (.08,.13) -2.26 .11 0.0000 <=.001
** femaleTRUE .74 (.61,.89) -.31 .1 0.0016 <=.01
*** singleTRUE 1.51 (1.35,1.68) .41 .06 0.0000 <=.001
*** poor_healthTRUE 1.35 (1.19,1.53) .3 .06 0.0000 <=.001
*** sedentaryTRUE 1.53 (1.37,1.7) .42 .05 0.0000 <=.001
*** current_work_2TRUE .77 (.67,.9) -.26 .08 0.0007 <=.001
*** current_drinkTRUE 1.46 (1.21,1.77) .38 .1 0.0001 <=.001
*** femaleFALSE:age_in_years_70 .96 (.96,.97) -.04 0 0.0000 <=.001
*** femaleTRUE:age_in_years_70 .95 (.94,.96) -.05 0 0.0000 <=.001
poor_healthTRUE:age_in_years_70 1 (.99,1.01) 0 .01 0.5072 > .10
poor_healthTRUE:current_work_2TRUE .79 (.6,1.04) -.23 .14 0.1001 > .10
. femaleFALSE:educ3_f( < HS ) 1.22 (.96,1.55) .2 .12 0.0987 <=.10
femaleTRUE:educ3_f( < HS ) 1.17 (.95,1.45) .16 .11 0.1384 > .10
femaleFALSE:educ3_f( HS < ) .8 (.59,1.1) -.22 .16 0.1726 > .10
femaleTRUE:educ3_f( HS < ) .85 (.63,1.14) -.16 .15 0.2884 > .10
current_drinkTRUE:educ3_f( < HS ) 1.02 (.81,1.3) .02 .12 0.8451 > .10
current_drinkTRUE:educ3_f( HS < ) .96 (.7,1.33) -.04 .17 0.8151 > .10

Contexts

session

sessionInfo()
R version 3.2.5 (2016-04-14)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] knitr_1.12.3  MASS_7.3-45   glmulti_1.0.7 rJava_0.9-8   ggplot2_2.1.0 magrittr_1.5 

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.5        RColorBrewer_1.1-2 formatR_1.3        plyr_1.8.3         highr_0.5.1        tools_3.2.5       
 [7] extrafont_0.17     digest_0.6.9       jsonlite_0.9.20    evaluate_0.9       gtable_0.2.0       DBI_0.4-1         
[13] yaml_2.1.13        parallel_3.2.5     Rttf2pt1_1.3.3     dplyr_0.4.3        stringr_1.0.0      htmlwidgets_0.6   
[19] grid_3.2.5         DT_0.1.40          R6_2.1.2           rmarkdown_0.9.6    tidyr_0.4.1        extrafontdb_1.0   
[25] scales_0.4.0       htmltools_0.3.5    rsconnect_0.4.2.1  assertthat_0.1     dichromat_2.0-0    testit_0.5        
[31] colorspace_1.2-6   stringi_1.0-1      lazyeval_0.1.10    munsell_0.4.3