rm(list=ls())
# Load libraries ---------------------------
library(haven)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(geeM)
## Loading required package: Matrix
# Set wd for generated output ---------------------------
setwd("/Volumes/caas/MERITS/RESOURCES/Data Processing/Data Analysis/Outcome Analyses 2016/Manuscript Revisions_2020/Aditya Khanna Analyses 2022/RESOURCES-AK-R")
# Load data ---------------------------
load(file="gee-formulae.RData")
# DV = AVCIG ---------------------------
#relevel MI and CBT
AVCIG_nobl_dt$MI_ref1 <- AVCIG_nobl_dt$MI %>% relevel("1")
AVCIG_nobl_dt$CBT_ref1 <- AVCIG_nobl_dt$CBT %>% relevel("1")
AVCIG_nobl_dt$TIME_ref1 <- AVCIG_nobl_dt$TIME %>% relevel("1")
## main model
AVCIG_nobl_main <- geem(formula = AVCIG.nobl.main,
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summary
summary(AVCIG_nobl_main)
## Estimates Model SE Robust SE wald p
## (Intercept) 1.77700 0.089150 0.11250 15.7900 0.00000
## cAGE -0.02810 0.039800 0.05864 -0.4791 0.63180
## cBLCGSMD 0.04724 0.004623 0.00517 9.1360 0.00000
## MI1 0.04773 0.087870 0.11300 0.4224 0.67270
## CBT1 -0.03620 0.088180 0.11260 -0.3215 0.74790
## TIME1 0.09405 0.087700 0.04884 1.9260 0.05413
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.8529
##
## Number of GEE iterations: 2
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
## interaction model
AVCIG_nobl_interaction <- geem(formula = AVCIG.nobl.interaction,
#mi=0, cbt=0, time=0
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_TIMEref1 <- geem(formula =
AVCIG ~ cAGE + cBLCGSMD + MI + CBT + TIME_ref1 + MI * CBT + MI * TIME_ref1 +
CBT * TIME_ref1 + MI * CBT * TIME_ref1,
#mi=0, cbt=0, time=1
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_MIref1 <-
geem(formula = AVCIG ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 * TIME +
CBT * TIME + MI_ref1 * CBT * TIME,
#ref: Mi=1, Cbt=0, Time=0
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_MIref1_TIMEref1 <-
geem(formula = AVCIG ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME_ref1 +
MI_ref1 * CBT + MI_ref1 * TIME_ref1 +
CBT * TIME_ref1 + MI_ref1 * CBT * TIME_ref1,
#ref: Mi=1, Cbt=0, Time=1
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_CBTref1 <-
geem(formula = AVCIG ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI *
TIME + CBT_ref1 * TIME + MI * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, Time = 0
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_CBTref1_TIMEref1 <-
geem(formula = AVCIG ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME_ref1 +
MI * CBT_ref1 + MI * TIME_ref1 + CBT_ref1 * TIME_ref1 + MI * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, Time = 1
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_MIref1_CBTref1 <-
geem(formula = AVCIG ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME + CBT_ref1 * TIME + MI_ref1 * CBT_ref1 * TIME,
#ref: Mi=1, Cbt=1, Time=0
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
AVCIG_nobl_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = AVCIG ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME_ref1 +
MI_ref1 * CBT_ref1 + MI_ref1 * TIME_ref1 +
CBT_ref1 * TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1,
#ref: Mi=1, Cbt=1, Time=1
data = AVCIG_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print interaction model summary
summary(AVCIG_nobl_interaction) #base: MI=0, CBT=0, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.87900 0.126500 0.141500 13.2800 0.0000
## cAGE -0.02613 0.039720 0.058870 -0.4440 0.6571
## cBLCGSMD 0.04854 0.004616 0.005141 9.4420 0.0000
## MI1 -0.19320 0.181500 0.184500 -1.0470 0.2949
## CBT1 -0.18940 0.172800 0.177700 -1.0660 0.2866
## TIME1 0.01963 0.181500 0.096760 0.2029 0.8392
## MI1:CBT1 0.35650 0.246100 0.242700 1.4690 0.1417
## MI1:TIME1 0.20920 0.259800 0.150000 1.3940 0.1632
## CBT1:TIME1 0.05884 0.246800 0.127500 0.4614 0.6445
## MI1:CBT1:TIME1 -0.21420 0.350900 0.196100 -1.0920 0.2748
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 2
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_TIMEref1) #base: MI=0, CBT=0, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.89900 0.130800 0.120700 15.72000 0.0000
## cAGE -0.02613 0.039720 0.058870 -0.44400 0.6571
## cBLCGSMD 0.04854 0.004616 0.005141 9.44200 0.0000
## MI1 0.01600 0.187100 0.186300 0.08587 0.9316
## CBT1 -0.13050 0.177300 0.169300 -0.77090 0.4408
## TIME_ref10 -0.01963 0.181500 0.096760 -0.20290 0.8392
## MI1:CBT1 0.14230 0.251800 0.247900 0.57410 0.5659
## MI1:TIME_ref10 -0.20920 0.259800 0.150000 -1.39400 0.1632
## CBT1:TIME_ref10 -0.05884 0.246800 0.127500 -0.46140 0.6445
## MI1:CBT1:TIME_ref10 0.21420 0.350900 0.196100 1.09200 0.2748
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 3
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_MIref1) #ref: MI=1, CBT=0, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.68600 0.129800 0.117300 14.370 0.00000
## cAGE -0.02613 0.039720 0.058870 -0.444 0.65710
## cBLCGSMD 0.04854 0.004616 0.005141 9.442 0.00000
## MI_ref10 0.19320 0.181500 0.184500 1.047 0.29490
## CBT1 0.16720 0.174800 0.164700 1.015 0.31010
## TIME1 0.22890 0.185800 0.113900 2.009 0.04456
## MI_ref10:CBT1 -0.35650 0.246100 0.242700 -1.469 0.14170
## MI_ref10:TIME1 -0.20920 0.259800 0.150000 -1.394 0.16320
## CBT1:TIME1 -0.15540 0.249400 0.148300 -1.048 0.29460
## MI_ref10:CBT1:TIME1 0.21420 0.350900 0.196100 1.092 0.27480
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 2
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.91500 0.133300 0.139000 13.77000 0.00000
## cAGE -0.02613 0.039720 0.058870 -0.44400 0.65710
## cBLCGSMD 0.04854 0.004616 0.005141 9.44200 0.00000
## MI_ref10 -0.01600 0.187100 0.186300 -0.08587 0.93160
## CBT1 0.01177 0.178100 0.179500 0.06557 0.94770
## TIME_ref10 -0.22890 0.185800 0.113900 -2.00900 0.04456
## MI_ref10:CBT1 -0.14230 0.251800 0.247900 -0.57410 0.56590
## MI_ref10:TIME_ref10 0.20920 0.259800 0.150000 1.39400 0.16320
## CBT1:TIME_ref10 0.15540 0.249400 0.148300 1.04800 0.29460
## MI_ref10:CBT1:TIME_ref10 -0.21420 0.350900 0.196100 -1.09200 0.27480
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 3
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_CBTref1) #ref: MI=0, CBT=1, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.690000 0.117500 0.109600 15.42000 0.0000
## cAGE -0.026130 0.039720 0.058870 -0.44400 0.6571
## cBLCGSMD 0.048540 0.004616 0.005141 9.44200 0.0000
## MI1 0.163300 0.165800 0.159100 1.02600 0.3048
## CBT_ref10 0.189400 0.172800 0.177700 1.06600 0.2866
## TIME1 0.078470 0.167100 0.083100 0.94440 0.3450
## MI1:CBT_ref10 -0.356500 0.246100 0.242700 -1.46900 0.1417
## MI1:TIME1 -0.004995 0.235800 0.126200 -0.03958 0.9684
## CBT_ref10:TIME1 -0.058840 0.246800 0.127500 -0.46140 0.6445
## MI1:CBT_ref10:TIME1 0.214200 0.350900 0.196100 1.09200 0.2748
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 2
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.768000 0.119300 0.119500 14.79000 0.0000
## cAGE -0.026130 0.039720 0.058870 -0.44400 0.6571
## cBLCGSMD 0.048540 0.004616 0.005141 9.44200 0.0000
## MI1 0.158300 0.167900 0.164700 0.96110 0.3365
## CBT_ref10 0.130500 0.177300 0.169300 0.77090 0.4408
## TIME_ref10 -0.078470 0.167100 0.083100 -0.94440 0.3450
## MI1:CBT_ref10 -0.142300 0.251800 0.247900 -0.57410 0.5659
## MI1:TIME_ref10 0.004995 0.235800 0.126200 0.03958 0.9684
## CBT_ref10:TIME_ref10 0.058840 0.246800 0.127500 0.46140 0.6445
## MI1:CBT_ref10:TIME_ref10 -0.214200 0.350900 0.196100 -1.09200 0.2748
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 2
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.853000 0.117000 0.116100 15.96000 0.0000
## cAGE -0.026130 0.039720 0.058870 -0.44400 0.6571
## cBLCGSMD 0.048540 0.004616 0.005141 9.44200 0.0000
## MI_ref10 -0.163300 0.165800 0.159100 -1.02600 0.3048
## CBT_ref10 -0.167200 0.174800 0.164700 -1.01500 0.3101
## TIME1 0.073480 0.166300 0.094920 0.77410 0.4389
## MI_ref10:CBT_ref10 0.356500 0.246100 0.242700 1.46900 0.1417
## MI_ref10:TIME1 0.004995 0.235800 0.126200 0.03958 0.9684
## CBT_ref10:TIME1 0.155400 0.249400 0.148300 1.04800 0.2946
## MI_ref10:CBT_ref10:TIME1 -0.214200 0.350900 0.196100 -1.09200 0.2748
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 2
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
summary(AVCIG_nobl_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.926000 0.118200 0.114900 16.77000 0.0000
## cAGE -0.026130 0.039720 0.058870 -0.44400 0.6571
## cBLCGSMD 0.048540 0.004616 0.005141 9.44200 0.0000
## MI_ref10 -0.158300 0.167900 0.164700 -0.96110 0.3365
## CBT_ref10 -0.011770 0.178100 0.179500 -0.06557 0.9477
## TIME_ref10 -0.073480 0.166300 0.094920 -0.77410 0.4389
## MI_ref10:CBT_ref10 0.142300 0.251800 0.247900 0.57410 0.5659
## MI_ref10:TIME_ref10 -0.004995 0.235800 0.126200 -0.03958 0.9684
## CBT_ref10:TIME_ref10 -0.155400 0.249400 0.148300 -1.04800 0.2946
## MI_ref10:CBT_ref10:TIME_ref10 0.214200 0.350900 0.196100 1.09200 0.2748
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.844
##
## Number of GEE iterations: 3
## Number of Clusters: 274 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 520
# DV = Cig/SmkD ---------------------------
#relevel MI and CBT
CGSMD_nobl_dt$MI_ref1 <- CGSMD_nobl_dt$MI %>% relevel("1")
CGSMD_nobl_dt$CBT_ref1 <- CGSMD_nobl_dt$CBT %>% relevel("1")
CGSMD_nobl_dt$TIME_ref1 <- CGSMD_nobl_dt$TIME %>% relevel("1")
## main model
CGSMD_nobl_main <- geem(formula = CGSMD.nobl.main,
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summary
summary(CGSMD_nobl_main)
## Estimates Model SE Robust SE wald p
## (Intercept) 1.956000 0.073540 0.091300 21.42000 0.00000
## cAGE -0.004485 0.033130 0.048740 -0.09201 0.92670
## cBLCGSMD 0.040940 0.003931 0.004366 9.37700 0.00000
## MI1 -0.005918 0.072870 0.092190 -0.06419 0.94880
## CBT1 0.015750 0.073040 0.092660 0.17000 0.86500
## TIME1 0.101100 0.072850 0.042640 2.37000 0.01778
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.562
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
## interaction model
CGSMD_nobl_interaction <- geem(formula = CGSMD.nobl.interaction,
#mi=0, cbt=0, time=0
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_TIMEref1 <- geem(formula =
CGSMD ~ cAGE + cBLCGSMD + MI + CBT + TIME_ref1 + MI * CBT + MI * TIME_ref1 +
CBT * TIME_ref1 + MI * CBT * TIME_ref1,
#mi=0, cbt=0, time=1
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_MIref1 <-
geem(formula = CGSMD ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 * TIME +
CBT * TIME + MI_ref1 * CBT * TIME,
#ref: Mi=1, Cbt=0, time=0
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_MIref1_TIMEref1 <-
geem(formula = CGSMD ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME_ref1 +
MI_ref1 * CBT + MI_ref1 * TIME_ref1 +
CBT * TIME_ref1 + MI_ref1 * CBT * TIME_ref1,
#ref: Mi=1, Cbt=0, time=1
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_CBTref1 <-
geem(formula = CGSMD ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI *
TIME + CBT_ref1 * TIME + MI * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, time=0
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_CBTref1_TIMEref1 <-
geem(formula = CGSMD ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME_ref1 + MI * CBT_ref1 + MI *
TIME_ref1 + CBT_ref1 * TIME_ref1 + MI * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, time=1
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_MIref1_CBTref1 <-
geem(formula = CGSMD ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME + CBT_ref1 * TIME + MI_ref1 * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, time=0
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
CGSMD_nobl_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = CGSMD ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME_ref1 + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME_ref1 + CBT_ref1 * TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, time=1
data = CGSMD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print interaction model summary
summary(CGSMD_nobl_interaction) #base: MI=0, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.045000 0.104800 0.116600 17.53000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI1 -0.181000 0.149600 0.153900 -1.17600 0.23970
## CBT1 -0.147300 0.142700 0.144400 -1.02000 0.30780
## TIME1 -0.001181 0.150800 0.085310 -0.01385 0.98900
## MI1:CBT1 0.311500 0.203500 0.200900 1.55000 0.12110
## MI1:TIME1 0.190600 0.213400 0.135600 1.40600 0.15970
## CBT1:TIME1 0.181600 0.207000 0.110800 1.63800 0.10140
## MI1:CBT1:TIME1 -0.328200 0.291100 0.172100 -1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_TIMEref1) #base: MI=0, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 2.044000 0.108700 0.102400 19.96000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI1 0.009634 0.153000 0.159000 0.06058 0.95170
## CBT1 0.034240 0.150800 0.135700 0.25230 0.80080
## TIME_ref10 0.001181 0.150800 0.085310 0.01385 0.98900
## MI1:CBT1 -0.016640 0.209300 0.205900 -0.08080 0.93560
## MI1:TIME_ref10 -0.190600 0.213400 0.135600 -1.40600 0.15970
## CBT1:TIME_ref10 -0.181600 0.207000 0.110800 -1.63800 0.10140
## MI1:CBT1:TIME_ref10 0.328200 0.291100 0.172100 1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_MIref1) #ref: MI=1, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.864000 0.106500 0.100300 18.58000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI_ref10 0.181000 0.149600 0.153900 1.17600 0.23970
## CBT1 0.164200 0.144800 0.140100 1.17200 0.24110
## TIME1 0.189400 0.151000 0.104600 1.81100 0.07020
## MI_ref10:CBT1 -0.311500 0.203500 0.200900 -1.55000 0.12110
## MI_ref10:TIME1 -0.190600 0.213400 0.135600 -1.40600 0.15970
## CBT1:TIME1 -0.146600 0.204600 0.131100 -1.11900 0.26330
## MI_ref10:CBT1:TIME1 0.328200 0.291100 0.172100 1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 2.053000 0.107300 0.120500 17.04000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI_ref10 -0.009634 0.153000 0.159000 -0.06058 0.95170
## CBT1 0.017600 0.144700 0.153800 0.11440 0.90890
## TIME_ref10 -0.189400 0.151000 0.104600 -1.81100 0.07020
## MI_ref10:CBT1 0.016640 0.209300 0.205900 0.08080 0.93560
## MI_ref10:TIME_ref10 0.190600 0.213400 0.135600 1.40600 0.15970
## CBT1:TIME_ref10 0.146600 0.204600 0.131100 1.11900 0.26330
## MI_ref10:CBT1:TIME_ref10 -0.328200 0.291100 0.172100 -1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_CBTref1) #ref: MI=0, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.898000 0.096630 0.086580 21.92000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI1 0.130500 0.137700 0.130500 1.00000 0.31730
## CBT_ref10 0.147300 0.142700 0.144400 1.02000 0.30780
## TIME1 0.180400 0.141900 0.070860 2.54600 0.01091
## MI1:CBT_ref10 -0.311500 0.203500 0.200900 -1.55000 0.12110
## MI1:TIME1 -0.137500 0.197900 0.106100 -1.29600 0.19490
## CBT_ref10:TIME1 -0.181600 0.207000 0.110800 -1.63800 0.10140
## MI1:CBT_ref10:TIME1 0.328200 0.291100 0.172100 1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 2.078000 0.104200 0.089790 23.14000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI1 -0.007003 0.142500 0.131000 -0.05345 0.95740
## CBT_ref10 -0.034240 0.150800 0.135700 -0.25230 0.80080
## TIME_ref10 -0.180400 0.141900 0.070860 -2.54600 0.01091
## MI1:CBT_ref10 0.016640 0.209300 0.205900 0.08080 0.93560
## MI1:TIME_ref10 0.137500 0.197900 0.106100 1.29600 0.19490
## CBT_ref10:TIME_ref10 0.181600 0.207000 0.110800 1.63800 0.10140
## MI1:CBT_ref10:TIME_ref10 -0.328200 0.291100 0.172100 -1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.028000 0.098080 0.098190 20.65000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI_ref10 -0.130500 0.137700 0.130500 -1.00000 0.31730
## CBT_ref10 -0.164200 0.144800 0.140100 -1.17200 0.24110
## TIME1 0.042840 0.138000 0.079050 0.54200 0.58790
## MI_ref10:CBT_ref10 0.311500 0.203500 0.200900 1.55000 0.12110
## MI_ref10:TIME1 0.137500 0.197900 0.106100 1.29600 0.19490
## CBT_ref10:TIME1 0.146600 0.204600 0.131100 1.11900 0.26330
## MI_ref10:CBT_ref10:TIME1 -0.328200 0.291100 0.172100 -1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
summary(CGSMD_nobl_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 2.071000 0.097140 0.096410 21.48000 0.00000
## cAGE -0.002582 0.033080 0.048820 -0.05289 0.95780
## cBLCGSMD 0.041710 0.003925 0.004326 9.64200 0.00000
## MI_ref10 0.007003 0.142500 0.131000 0.05345 0.95740
## CBT_ref10 -0.017600 0.144700 0.153800 -0.11440 0.90890
## TIME_ref10 -0.042840 0.138000 0.079050 -0.54200 0.58790
## MI_ref10:CBT_ref10 -0.016640 0.209300 0.205900 -0.08080 0.93560
## MI_ref10:TIME_ref10 -0.137500 0.197900 0.106100 -1.29600 0.19490
## CBT_ref10:TIME_ref10 -0.146600 0.204600 0.131100 -1.11900 0.26330
## MI_ref10:CBT_ref10:TIME_ref10 0.328200 0.291100 0.172100 1.90700 0.05653
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.5571
##
## Number of GEE iterations: 2
## Number of Clusters: 268 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 484
# DV = PCSMKD ---------------------------
#relevel MI and CBT
PCSMKD_nobl_dt$MI_ref1 <- PCSMKD_nobl_dt$MI %>% relevel("1")
PCSMKD_nobl_dt$CBT_ref1 <- PCSMKD_nobl_dt$CBT %>% relevel("1")
PCSMKD_nobl_dt$TIME_ref1 <- PCSMKD_nobl_dt$TIME %>% relevel("1")
# check contrasts
contrasts(PCSMKD_nobl_dt$MI) #ref: MI=0
## 1
## 0 0
## 1 1
contrasts(PCSMKD_nobl_dt$MI_ref1) #ref: MI=1
## 0
## 1 0
## 0 1
contrasts(PCSMKD_nobl_dt$CBT) #ref: CBT=0
## 1
## 0 0
## 1 1
contrasts(PCSMKD_nobl_dt$CBT_ref1) #ref: CBT=1
## 0
## 1 0
## 0 1
## fit main model
PCSMKD_nobl_main <- geem(formula = PCSMKD.nobl.main,
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summary
summary(PCSMKD_nobl_main) #ref: Mi=0, Cbt=0
## Estimates Model SE Robust SE wald p
## (Intercept) 4.355000 0.038350 0.043910 99.2000 0.00000
## cAGE 0.015680 0.017230 0.022700 0.6909 0.48960
## cBLCGSMD 0.006944 0.002055 0.002978 2.3320 0.01972
## MI1 0.088370 0.037970 0.046690 1.8930 0.05838
## CBT1 -0.071120 0.038100 0.046540 -1.5280 0.12650
## TIME1 0.010900 0.037910 0.024880 0.4380 0.66140
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1828
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
## fit MI and CBT 2-way interactions
PCSMKD_MI_interactions <- geem(formula = PCSMDK.MI.interaction,
#ref: Mi=0, Cbt=0
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_MI_interactions_MIref1_CBT_ref0 <-
geem(PCSMKD ~ cAGE + cBLCGSMD + MI_ref1*TIME + CBT,
#ref: Mi=1, Cbt=0
data = PCSMKD_nobl_dt ,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_CBT_interactions <- geem(formula = PCSMDK.CBT.interaction,
#ref: Mi=0, Cbt=0
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summaries
summary(PCSMKD_MI_interactions)
## Estimates Model SE Robust SE wald p
## (Intercept) 4.376000 0.042560 0.044970 97.3300 0.00000
## cAGE 0.015420 0.017260 0.022740 0.6780 0.49780
## cBLCGSMD 0.006929 0.002059 0.002985 2.3210 0.02028
## MI1 0.046410 0.053010 0.052430 0.8853 0.37600
## CBT1 -0.072190 0.038160 0.046590 -1.5500 0.12120
## TIME1 -0.032010 0.053510 0.036980 -0.8655 0.38680
## MI1:TIME1 0.086340 0.075940 0.049790 1.7340 0.08287
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1835
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_MI_interactions_MIref1_CBT_ref0)
## Estimates Model SE Robust SE wald p
## (Intercept) 4.423000 0.043090 0.041270 107.2000 0.00000
## cAGE 0.015420 0.017260 0.022740 0.6780 0.49780
## cBLCGSMD 0.006929 0.002059 0.002985 2.3210 0.02028
## MI_ref10 -0.046410 0.053010 0.052430 -0.8853 0.37600
## TIME1 0.054340 0.053890 0.033310 1.6310 0.10280
## CBT1 -0.072190 0.038160 0.046590 -1.5500 0.12120
## MI_ref10:TIME1 -0.086340 0.075940 0.049790 -1.7340 0.08287
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1835
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_CBT_interactions)
## Estimates Model SE Robust SE wald p
## (Intercept) 4.329000 0.04344 0.047380 91.3600 0.00000
## cAGE 0.015270 0.01727 0.022710 0.6723 0.50140
## cBLCGSMD 0.006982 0.00206 0.002979 2.3440 0.01910
## MI1 0.089610 0.03805 0.046750 1.9170 0.05526
## CBT1 -0.023990 0.05322 0.052940 -0.4532 0.65040
## TIME1 0.063770 0.05641 0.034260 1.8610 0.06270
## CBT1:TIME1 -0.096820 0.07631 0.049260 -1.9660 0.04935
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1836
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
## fit 3-way interaction model
PCSMKD_nobl_interaction <-
geem(formula = PCSMKD.nobl.interaction,
#ref: Mi=0, Cbt=0, time=0
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_TIMEref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI + CBT + TIME_ref1 + MI * CBT + MI *
TIME_ref1 + CBT * TIME_ref1 + MI * CBT * TIME_ref1,
#ref: Mi=0, Cbt=0, time=1
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_MIref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 *
TIME + CBT * TIME + MI_ref1 * CBT * TIME,
#ref: Mi=1, Cbt=0, time=0
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_MIref1_TIMEref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME_ref1 + MI_ref1 * CBT + MI_ref1 *
TIME_ref1 + CBT * TIME_ref1 + MI_ref1 * CBT * TIME_ref1,
#ref: Mi=1, Cbt=0, time=1
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_CBTref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI *
TIME + CBT_ref1 * TIME + MI * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, time=0
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_CBTref1_TIMEref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME_ref1 + MI * CBT_ref1 + MI *
TIME_ref1 + CBT_ref1 * TIME_ref1 + MI * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, time=1
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_MIref1_CBTref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME + CBT_ref1 * TIME + MI_ref1 * CBT_ref1 * TIME,
#ref: Mi=1, Cbt=1, time=0
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
PCSMKD_nobl_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = PCSMKD ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME_ref1 + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME_ref1 + CBT_ref1 * TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1,
#ref: Mi=1, Cbt=1, time=1
data = PCSMKD_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print interaction model summary
summary(PCSMKD_nobl_interaction) #base: MI=0, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 4.349000 0.055160 0.058660 74.14000 0.00000
## cAGE 0.016360 0.017380 0.022890 0.71470 0.47480
## cBLCGSMD 0.007199 0.002074 0.002995 2.40400 0.01624
## MI1 0.048660 0.078950 0.075900 0.64110 0.52150
## CBT1 -0.021210 0.075230 0.079020 -0.26840 0.78840
## TIME1 0.066670 0.079100 0.053380 1.24900 0.21160
## MI1:CBT1 -0.005168 0.107100 0.105500 -0.04898 0.96090
## MI1:TIME1 -0.006297 0.113300 0.067540 -0.09324 0.92570
## CBT1:TIME1 -0.186700 0.107800 0.073480 -2.54100 0.01106
## MI1:CBT1:TIME1 0.175000 0.153200 0.097850 1.78900 0.07362
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_TIMEref1) #base: MI=0, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 4.415000 0.057020 0.052760 83.68000 0.00000
## cAGE 0.016360 0.017380 0.022890 0.71470 0.47480
## cBLCGSMD 0.007199 0.002074 0.002995 2.40400 0.01624
## MI1 0.042360 0.081790 0.066150 0.64040 0.52190
## CBT1 -0.207900 0.077670 0.086540 -2.40200 0.01630
## TIME_ref10 -0.066670 0.079100 0.053380 -1.24900 0.21160
## MI1:CBT1 0.169900 0.110300 0.105900 1.60400 0.10870
## MI1:TIME_ref10 0.006297 0.113300 0.067540 0.09324 0.92570
## CBT1:TIME_ref10 0.186700 0.107800 0.073480 2.54100 0.01106
## MI1:CBT1:TIME_ref10 -0.175000 0.153200 0.097850 -1.78900 0.07362
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_MIref1) #ref: MI=1, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 4.397000 0.056360 0.048050 91.52000 0.00000
## cAGE 0.016360 0.017380 0.022890 0.71470 0.47480
## cBLCGSMD 0.007199 0.002074 0.002995 2.40400 0.01624
## MI_ref10 -0.048660 0.078950 0.075900 -0.64110 0.52150
## CBT1 -0.026370 0.076030 0.069800 -0.37790 0.70550
## TIME1 0.060380 0.081110 0.041420 1.45800 0.14500
## MI_ref10:CBT1 0.005168 0.107100 0.105500 0.04898 0.96090
## MI_ref10:TIME1 0.006297 0.113300 0.067540 0.09324 0.92570
## CBT1:TIME1 -0.011640 0.108900 0.064650 -0.18010 0.85710
## MI_ref10:CBT1:TIME1 -0.175000 0.153200 0.097850 -1.78900 0.07362
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 4.458000 0.058410 0.039160 113.80000 0.00000
## cAGE 0.016360 0.017380 0.022890 0.71470 0.47480
## cBLCGSMD 0.007199 0.002074 0.002995 2.40400 0.01624
## MI_ref10 -0.042360 0.081790 0.066150 -0.64040 0.52190
## CBT1 -0.038020 0.078030 0.060480 -0.62860 0.52960
## TIME_ref10 -0.060380 0.081110 0.041420 -1.45800 0.14500
## MI_ref10:CBT1 -0.169900 0.110300 0.105900 -1.60400 0.10870
## MI_ref10:TIME_ref10 -0.006297 0.113300 0.067540 -0.09324 0.92570
## CBT1:TIME_ref10 0.011640 0.108900 0.064650 0.18010 0.85710
## MI_ref10:CBT1:TIME_ref10 0.175000 0.153200 0.097850 1.78900 0.07362
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_CBTref1) #ref: MI=0, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 4.328000 0.051050 0.052200 82.91000 0.00000
## cAGE 0.016360 0.017380 0.022890 0.71470 0.47480
## cBLCGSMD 0.007199 0.002074 0.002995 2.40400 0.01624
## MI1 0.043490 0.072190 0.072590 0.59910 0.54910
## CBT_ref10 0.021210 0.075230 0.079020 0.26840 0.78840
## TIME1 -0.120000 0.073250 0.050700 -2.36700 0.01793
## MI1:CBT_ref10 0.005168 0.107100 0.105500 0.04898 0.96090
## MI1:TIME1 0.168700 0.103200 0.070980 2.37800 0.01743
## CBT_ref10:TIME1 0.186700 0.107800 0.073480 2.54100 0.01106
## MI1:CBT_ref10:TIME1 -0.175000 0.153200 0.097850 -1.78900 0.07362
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 4.208000 0.052590 0.067960 61.9100 0.000000
## cAGE 0.016360 0.017380 0.022890 0.7147 0.474800
## cBLCGSMD 0.007199 0.002074 0.002995 2.4040 0.016240
## MI1 0.212200 0.073810 0.082030 2.5870 0.009673
## CBT_ref10 0.207900 0.077670 0.086540 2.4020 0.016300
## TIME_ref10 0.120000 0.073250 0.050700 2.3670 0.017930
## MI1:CBT_ref10 -0.169900 0.110300 0.105900 -1.6040 0.108700
## MI1:TIME_ref10 -0.168700 0.103200 0.070980 -2.3780 0.017430
## CBT_ref10:TIME_ref10 -0.186700 0.107800 0.073480 -2.5410 0.011060
## MI1:CBT_ref10:TIME_ref10 0.175000 0.153200 0.097850 1.7890 0.073620
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 4.371000 0.051020 0.050660 86.29000 0.00000
## cAGE 0.016360 0.017380 0.022890 0.71470 0.47480
## cBLCGSMD 0.007199 0.002074 0.002995 2.40400 0.01624
## MI_ref10 -0.043490 0.072190 0.072590 -0.59910 0.54910
## CBT_ref10 0.026370 0.076030 0.069800 0.37790 0.70550
## TIME1 0.048730 0.072650 0.049700 0.98050 0.32680
## MI_ref10:CBT_ref10 -0.005168 0.107100 0.105500 -0.04898 0.96090
## MI_ref10:TIME1 -0.168700 0.103200 0.070980 -2.37800 0.01743
## CBT_ref10:TIME1 0.011640 0.108900 0.064650 0.18010 0.85710
## MI_ref10:CBT_ref10:TIME1 0.175000 0.153200 0.097850 1.78900 0.07362
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
summary(PCSMKD_nobl_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 4.420000 0.051740 0.046370 95.3100 0.000000
## cAGE 0.016360 0.017380 0.022890 0.7147 0.474800
## cBLCGSMD 0.007199 0.002074 0.002995 2.4040 0.016240
## MI_ref10 -0.212200 0.073810 0.082030 -2.5870 0.009673
## CBT_ref10 0.038020 0.078030 0.060480 0.6286 0.529600
## TIME_ref10 -0.048730 0.072650 0.049700 -0.9805 0.326800
## MI_ref10:CBT_ref10 0.169900 0.110300 0.105900 1.6040 0.108700
## MI_ref10:TIME_ref10 0.168700 0.103200 0.070980 2.3780 0.017430
## CBT_ref10:TIME_ref10 -0.011640 0.108900 0.064650 -0.1801 0.857100
## MI_ref10:CBT_ref10:TIME_ref10 -0.175000 0.153200 0.097850 -1.7890 0.073620
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.185
##
## Number of GEE iterations: 2
## Number of Clusters: 273 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 516
# DV = PPVABS ---------------------------
#relevel MI and CBT
PPVABS_nobl_dt$MI_ref1 <- PPVABS_nobl_dt$MI %>% relevel("1")
PPVABS_nobl_dt$CBT_ref1 <- PPVABS_nobl_dt$CBT %>% relevel("1")
PPVABS_nobl_dt$TIME_ref1 <- PPVABS_nobl_dt$TIME %>% relevel("1")
## fit main model
PPVABS_nobl_main <- geem(formula = PPVABS.nobl.main,
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
## print model summary
summary(PPVABS_nobl_main)
## Estimates Model SE Robust SE wald p
## (Intercept) -1.37700 0.21090 0.24260 -5.6740 1.000e-08
## cAGE -0.35500 0.09446 0.09903 -3.5850 3.372e-04
## cBLCGSMD -0.02391 0.01224 0.01855 -1.2890 1.975e-01
## MI1 -0.09577 0.20580 0.25370 -0.3776 7.057e-01
## CBT1 0.17260 0.20670 0.26010 0.6638 5.068e-01
## TIME1 -0.04156 0.20490 0.13470 -0.3086 7.576e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.01
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
## fit 3-way interaction model
PPVABS_nobl_interaction <-
geem(formula = PPVABS.nobl.interaction,
#ref: Mi=0, Cbt=0, time=0
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_TIMEref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI + CBT + TIME_ref1 + MI * CBT + MI *
TIME_ref1 + CBT * TIME_ref1 + MI * CBT * TIME_ref1,
#ref: Mi=0, Cbt=0, time=1
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_MIref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 *
TIME + CBT * TIME + MI_ref1 * CBT * TIME,
#ref: Mi=1, Cbt=0, time=0
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_MIref1_TIMEref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME_ref1 + MI_ref1 * CBT + MI_ref1 *
TIME_ref1 + CBT * TIME_ref1 + MI_ref1 * CBT * TIME_ref1,
#ref: Mi=1, Cbt=0, time=1
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_CBTref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI *
TIME + CBT_ref1 * TIME + MI * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, time=0
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_CBTref1_TIMEref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME_ref1 + MI * CBT_ref1 + MI *
TIME_ref1 + CBT_ref1 * TIME_ref1 + MI * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, time=1
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_MIref1_CBTref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME + CBT_ref1 * TIME + MI_ref1 * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, time=0
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
PPVABS_nobl_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = PPVABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME_ref1 + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME_ref1 + CBT_ref1 * TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, time=1
data = PPVABS_nobl_dt,
id=id,
family = binomial
)
## print interaction model summary
summary(PPVABS_nobl_interaction) #base: MI=0, CBT=0, TIME=0
## Estimates Model SE Robust SE wald p
## (Intercept) -1.36000 0.29890 0.30170 -4.50600 6.590e-06
## cAGE -0.35670 0.09533 0.09861 -3.61700 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.28200 1.999e-01
## MI1 -0.40360 0.45830 0.46130 -0.87490 3.816e-01
## CBT1 0.17490 0.40140 0.40420 0.43260 6.653e-01
## TIME1 -0.08703 0.42040 0.26090 -0.33360 7.387e-01
## MI1:CBT1 0.44550 0.59550 0.59550 0.74820 4.544e-01
## MI1:TIME1 0.59840 0.62370 0.45090 1.32700 1.845e-01
## CBT1:TIME1 0.01350 0.57100 0.35700 0.03781 9.698e-01
## MI1:CBT1:TIME1 -0.90760 0.83390 0.56070 -1.61900 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_TIMEref1) #base: MI=0, CBT=0, TIME=1
## Estimates Model SE Robust SE wald p
## (Intercept) -1.44700 0.30550 0.31400 -4.60700 4.090e-06
## cAGE -0.35670 0.09533 0.09861 -3.61700 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.28200 1.999e-01
## MI1 0.19480 0.42710 0.43130 0.45170 6.515e-01
## CBT1 0.18840 0.40950 0.41440 0.45450 6.495e-01
## TIME_ref10 0.08703 0.42040 0.26090 0.33360 7.387e-01
## MI1:CBT1 -0.46210 0.58820 0.58590 -0.78860 4.303e-01
## MI1:TIME_ref10 -0.59840 0.62370 0.45090 -1.32700 1.845e-01
## CBT1:TIME_ref10 -0.01350 0.57100 0.35700 -0.03781 9.698e-01
## MI1:CBT1:TIME_ref10 0.90760 0.83390 0.56070 1.61900 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_MIref1) #ref: MI=1, CBT=0, TIME=0
## Estimates Model SE Robust SE wald p
## (Intercept) -1.76300 0.35010 0.35920 -4.9090 9.200e-07
## cAGE -0.35670 0.09533 0.09861 -3.6170 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.2820 1.999e-01
## MI_ref10 0.40360 0.45830 0.46130 0.8749 3.816e-01
## CBT1 0.62040 0.43930 0.43990 1.4100 1.585e-01
## TIME1 0.51130 0.46070 0.36730 1.3920 1.639e-01
## MI_ref10:CBT1 -0.44550 0.59550 0.59550 -0.7482 4.544e-01
## MI_ref10:TIME1 -0.59840 0.62370 0.45090 -1.3270 1.845e-01
## CBT1:TIME1 -0.89410 0.60780 0.43160 -2.0720 3.830e-02
## MI_ref10:CBT1:TIME1 0.90760 0.83390 0.56070 1.6190 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, TIME=1
## Estimates Model SE Robust SE wald p
## (Intercept) -1.25200 0.30030 0.30690 -4.0790 4.531e-05
## cAGE -0.35670 0.09533 0.09861 -3.6170 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.2820 1.999e-01
## MI_ref10 -0.19480 0.42710 0.43130 -0.4517 6.515e-01
## CBT1 -0.27370 0.42040 0.41610 -0.6578 5.107e-01
## TIME_ref10 -0.51130 0.46070 0.36730 -1.3920 1.639e-01
## MI_ref10:CBT1 0.46210 0.58820 0.58590 0.7886 4.303e-01
## MI_ref10:TIME_ref10 0.59840 0.62370 0.45090 1.3270 1.845e-01
## CBT1:TIME_ref10 0.89410 0.60780 0.43160 2.0720 3.830e-02
## MI_ref10:CBT1:TIME_ref10 -0.90760 0.83390 0.56070 -1.6190 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_CBTref1) #ref: MI=0, CBT=1, TIME=0
## Estimates Model SE Robust SE wald p
## (Intercept) -1.18500 0.27130 0.26960 -4.39500 1.108e-05
## cAGE -0.35670 0.09533 0.09861 -3.61700 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.28200 1.999e-01
## MI1 0.04195 0.37980 0.37290 0.11250 9.104e-01
## CBT_ref10 -0.17490 0.40140 0.40420 -0.43260 6.653e-01
## TIME1 -0.07353 0.38640 0.24370 -0.30170 7.629e-01
## MI1:CBT_ref10 -0.44550 0.59550 0.59550 -0.74820 4.544e-01
## MI1:TIME1 -0.30920 0.55350 0.33300 -0.92870 3.531e-01
## CBT_ref10:TIME1 -0.01350 0.57100 0.35700 -0.03781 9.698e-01
## MI1:CBT_ref10:TIME1 0.90760 0.83390 0.56070 1.61900 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, TIME=1
## Estimates Model SE Robust SE wald p
## (Intercept) -1.25800 0.27640 0.27080 -4.64700 3.360e-06
## cAGE -0.35670 0.09533 0.09861 -3.61700 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.28200 1.999e-01
## MI1 -0.26730 0.40330 0.39300 -0.68010 4.964e-01
## CBT_ref10 -0.18840 0.40950 0.41440 -0.45450 6.495e-01
## TIME_ref10 0.07353 0.38640 0.24370 0.30170 7.629e-01
## MI1:CBT_ref10 0.46210 0.58820 0.58590 0.78860 4.303e-01
## MI1:TIME_ref10 0.30920 0.55350 0.33300 0.92870 3.531e-01
## CBT_ref10:TIME_ref10 0.01350 0.57100 0.35700 0.03781 9.698e-01
## MI1:CBT_ref10:TIME_ref10 -0.90760 0.83390 0.56070 -1.61900 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, TIME=0
## Estimates Model SE Robust SE wald p
## (Intercept) -1.14300 0.26710 0.25720 -4.4440 8.830e-06
## cAGE -0.35670 0.09533 0.09861 -3.6170 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.2820 1.999e-01
## MI_ref10 -0.04195 0.37980 0.37290 -0.1125 9.104e-01
## CBT_ref10 -0.62040 0.43930 0.43990 -1.4100 1.585e-01
## TIME1 -0.38280 0.39630 0.22670 -1.6890 9.130e-02
## MI_ref10:CBT_ref10 0.44550 0.59550 0.59550 0.7482 4.544e-01
## MI_ref10:TIME1 0.30920 0.55350 0.33300 0.9287 3.531e-01
## CBT_ref10:TIME1 0.89410 0.60780 0.43160 2.0720 3.830e-02
## MI_ref10:CBT_ref10:TIME1 -0.90760 0.83390 0.56070 -1.6190 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
summary(PPVABS_nobl_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, TIME=1
## Estimates Model SE Robust SE wald p
## (Intercept) -1.52600 0.29550 0.28330 -5.3860 7.000e-08
## cAGE -0.35670 0.09533 0.09861 -3.6170 2.978e-04
## cBLCGSMD -0.02402 0.01231 0.01874 -1.2820 1.999e-01
## MI_ref10 0.26730 0.40330 0.39300 0.6801 4.964e-01
## CBT_ref10 0.27370 0.42040 0.41610 0.6578 5.107e-01
## TIME_ref10 0.38280 0.39630 0.22670 1.6890 9.130e-02
## MI_ref10:CBT_ref10 -0.46210 0.58820 0.58590 -0.7886 4.303e-01
## MI_ref10:TIME_ref10 -0.30920 0.55350 0.33300 -0.9287 3.531e-01
## CBT_ref10:TIME_ref10 -0.89410 0.60780 0.43160 -2.0720 3.830e-02
## MI_ref10:CBT_ref10:TIME_ref10 0.90760 0.83390 0.56070 1.6190 1.055e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 1.015
##
## Number of GEE iterations: 2
## Number of Clusters: 295 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 590
# DV: NCIGS ---------------------------
#relevel MI and CBT
ncigs_dt_na.omit$MI_ref1 <- ncigs_dt_na.omit$MI %>% relevel("1")
ncigs_dt_na.omit$CBT_ref1 <- ncigs_dt_na.omit$CBT %>% relevel("1")
ncigs_dt_na.omit$TIME_ref1 <- ncigs_dt_na.omit$TIME %>% relevel("1")
ncigs_dt_na.omit$TIME_ref2 <- ncigs_dt_na.omit$TIME %>% relevel("2")
## fit main model
ncigs_main <- geem(formula = ncigs.main,
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
## print model summary
summary(ncigs_main)
## Estimates Model SE Robust SE wald p
## (Intercept) 2.388000 0.07925 0.08408 28.40000 0.00000
## cAGE 0.114700 0.03195 0.04717 2.43200 0.01503
## MI1 0.049220 0.07124 0.09912 0.49660 0.61950
## CBT1 -0.003666 0.07137 0.10160 -0.03607 0.97120
## TIME1 -0.538000 0.08603 0.06840 -7.86500 0.00000
## TIME2 -0.466700 0.08698 0.07019 -6.64800 0.00000
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9935
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
## fit 3-way interaction model
ncigs_interaction <- geem(formula = ncigs.interaction,
#ref: Mi=0, Cbt=0, time=0
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_TIMEref1 <- geem(formula =
NCIGS ~ cAGE + MI + CBT + TIME_ref1 + MI * CBT + MI * TIME_ref1 + CBT *
TIME_ref1 + MI * CBT * TIME_ref1 + offset(log_unctrldays),
#ref: Mi=0, Cbt=0, time=1
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_TIMEref2 <- geem(formula =
NCIGS ~ cAGE + MI + CBT + TIME_ref2 + MI * CBT + MI * TIME_ref2 + CBT *
TIME_ref2 + MI * CBT * TIME_ref2 + offset(log_unctrldays),
#ref: Mi=0, Cbt=0, time=1
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_MIref1 <-
geem(formula = NCIGS ~ cAGE + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 * TIME + CBT *
TIME + MI_ref1 * CBT * TIME + offset(log_unctrldays),
#ref: Mi=1, Cbt=0, time=0
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_MIref1_TIMEref1 <-
geem(formula = NCIGS ~ cAGE + MI_ref1 + CBT + TIME_ref1 + MI_ref1 * CBT + MI_ref1 * TIME_ref1 + CBT *
TIME_ref1 + MI_ref1 * CBT * TIME_ref1 + offset(log_unctrldays),
#ref: Mi=1, Cbt=0, time=1
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_MIref1_TIMEref2 <-
geem(formula = NCIGS ~ cAGE + MI_ref1 + CBT + TIME_ref2 + MI_ref1 * CBT + MI_ref1 * TIME_ref2 + CBT *
TIME_ref2 + MI_ref1 * CBT * TIME_ref2 + offset(log_unctrldays),
#ref: Mi=1, Cbt=0, time=2
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_CBTref1 <-
geem(formula = NCIGS ~ cAGE + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI * TIME + CBT_ref1 *
TIME + MI * CBT_ref1 * TIME + offset(log_unctrldays),
#ref: Mi=0, Cbt=1, time=0
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_CBTref1_TIMEref1 <-
geem(formula = NCIGS ~ cAGE + MI + CBT_ref1 + TIME_ref1 + MI * CBT_ref1 + MI * TIME_ref1 + CBT_ref1 *
TIME_ref1 + MI * CBT_ref1 * TIME_ref1 + offset(log_unctrldays),
#ref: Mi=0, Cbt=1, time=1
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_CBTref1_TIMEref2 <-
geem(formula = NCIGS ~ cAGE + MI + CBT_ref1 + TIME_ref2 + MI * CBT_ref1 + MI * TIME_ref2 + CBT_ref1 *
TIME_ref2 + MI * CBT_ref1 * TIME_ref2 + offset(log_unctrldays),
#ref: Mi=0, Cbt=1, time=2
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_MIref1_CBTref1 <-
geem(formula = NCIGS ~ cAGE + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 * TIME + CBT_ref1 *
TIME + MI_ref1 * CBT_ref1 * TIME + offset(log_unctrldays),
#ref: MI_ref1=1, Cbt=1, time=0
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = NCIGS ~ cAGE + MI_ref1 + CBT_ref1 + TIME_ref1 + MI_ref1 * CBT_ref1 + MI_ref1 * TIME_ref1 + CBT_ref1 *
TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1 + offset(log_unctrldays),
#ref: MI_ref1=1, Cbt=1, time=1
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
ncigs_interaction_MIref1_CBTref1_TIMEref2 <-
geem(formula = NCIGS ~ cAGE + MI_ref1 + CBT_ref1 + TIME_ref2 + MI_ref1 * CBT_ref1 + MI_ref1 * TIME_ref2 + CBT_ref1 *
TIME_ref2 + MI_ref1 * CBT_ref1 * TIME_ref2 + offset(log_unctrldays),
#ref: MI_ref1=1, Cbt=1, time=2
data = ncigs_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
## print model summary
summary(ncigs_interaction) #ref: MI=0, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.3230 0.12390 0.12020 19.3400 0.000000
## cAGE 0.1139 0.03201 0.04747 2.3990 0.016460
## MI1 0.1224 0.17670 0.15320 0.7989 0.424400
## CBT1 0.1758 0.16860 0.15800 1.1120 0.265900
## TIME1 -0.4595 0.17710 0.17510 -2.6230 0.008703
## TIME2 -0.4610 0.18020 0.16150 -2.8550 0.004300
## MI1:CBT1 -0.2682 0.24020 0.20320 -1.3200 0.186900
## MI1:TIME1 -0.1059 0.25370 0.21800 -0.4856 0.627300
## MI1:TIME2 0.1067 0.25750 0.20830 0.5122 0.608500
## CBT1:TIME1 -0.1986 0.24180 0.21650 -0.9173 0.359000
## CBT1:TIME2 -0.1559 0.24530 0.21830 -0.7141 0.475200
## MI1:CBT1:TIME1 0.3147 0.34480 0.27670 1.1370 0.255500
## MI1:CBT1:TIME2 0.1038 0.34880 0.27940 0.3714 0.710400
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_TIMEref1) #ref: MI=0, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.864000 0.12710 0.14060 13.26000 0.000000
## cAGE 0.113900 0.03201 0.04747 2.39900 0.016460
## MI1 0.016560 0.18270 0.21460 0.07713 0.938500
## CBT1 -0.022860 0.17380 0.19020 -0.12020 0.904300
## TIME_ref10 0.459500 0.17710 0.17510 2.62300 0.008703
## TIME_ref12 -0.001503 0.18240 0.08536 -0.01760 0.986000
## MI1:CBT1 0.046410 0.24790 0.27500 0.16880 0.866000
## MI1:TIME_ref10 0.105900 0.25370 0.21800 0.48560 0.627300
## MI1:TIME_ref12 0.212600 0.26180 0.13660 1.55600 0.119800
## CBT1:TIME_ref10 0.198600 0.24180 0.21650 0.91730 0.359000
## CBT1:TIME_ref12 0.042750 0.24880 0.11850 0.36090 0.718200
## MI1:CBT1:TIME_ref10 -0.314700 0.34480 0.27670 -1.13700 0.255500
## MI1:CBT1:TIME_ref12 -0.210900 0.35420 0.18190 -1.15900 0.246300
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_TIMEref2) #ref: MI=0, CBT=0, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) 1.862000 0.13120 0.13120 14.2000 0.00000
## cAGE 0.113900 0.03201 0.04747 2.3990 0.01646
## MI1 0.229100 0.18810 0.20110 1.1390 0.25460
## CBT1 0.019890 0.17850 0.19030 0.1045 0.91680
## TIME_ref20 0.461000 0.18020 0.16150 2.8550 0.00430
## TIME_ref21 0.001503 0.18240 0.08536 0.0176 0.98600
## MI1:CBT1 -0.164500 0.25350 0.26820 -0.6133 0.53970
## MI1:TIME_ref20 -0.106700 0.25750 0.20830 -0.5122 0.60850
## MI1:TIME_ref21 -0.212600 0.26180 0.13660 -1.5560 0.11980
## CBT1:TIME_ref20 0.155900 0.24530 0.21830 0.7141 0.47520
## CBT1:TIME_ref21 -0.042750 0.24880 0.11850 -0.3609 0.71820
## MI1:CBT1:TIME_ref20 -0.103800 0.34880 0.27940 -0.3714 0.71040
## MI1:CBT1:TIME_ref21 0.210900 0.35420 0.18190 1.1590 0.24630
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_MIref1) #ref: MI=1, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.44600 0.12560 0.09504 25.7300 0.000e+00
## cAGE 0.11390 0.03201 0.04747 2.3990 1.646e-02
## MI_ref10 -0.12240 0.17670 0.15320 -0.7989 4.244e-01
## CBT1 -0.09249 0.17090 0.12650 -0.7310 4.648e-01
## TIME1 -0.56540 0.18160 0.12950 -4.3650 1.272e-05
## TIME2 -0.35430 0.18400 0.13190 -2.6870 7.217e-03
## MI_ref10:CBT1 0.26820 0.24020 0.20320 1.3200 1.869e-01
## MI_ref10:TIME1 0.10590 0.25370 0.21800 0.4856 6.273e-01
## MI_ref10:TIME2 -0.10670 0.25750 0.20830 -0.5122 6.085e-01
## CBT1:TIME1 0.11600 0.24580 0.17210 0.6741 5.002e-01
## CBT1:TIME2 -0.05211 0.24800 0.17440 -0.2988 7.651e-01
## MI_ref10:CBT1:TIME1 -0.31470 0.34480 0.27670 -1.1370 2.555e-01
## MI_ref10:CBT1:TIME2 -0.10380 0.34880 0.27940 -0.3714 7.104e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.88000 0.13120 0.16300 11.54000 0.000e+00
## cAGE 0.11390 0.03201 0.04747 2.39900 1.646e-02
## MI_ref10 -0.01656 0.18270 0.21460 -0.07713 9.385e-01
## CBT1 0.02355 0.17670 0.19900 0.11830 9.058e-01
## TIME_ref10 0.56540 0.18160 0.12950 4.36500 1.272e-05
## TIME_ref12 0.21100 0.18780 0.10700 1.97300 4.850e-02
## MI_ref10:CBT1 -0.04641 0.24790 0.27500 -0.16880 8.660e-01
## MI_ref10:TIME_ref10 -0.10590 0.25370 0.21800 -0.48560 6.273e-01
## MI_ref10:TIME_ref12 -0.21260 0.26180 0.13660 -1.55600 1.198e-01
## CBT1:TIME_ref10 -0.11600 0.24580 0.17210 -0.67410 5.002e-01
## CBT1:TIME_ref12 -0.16820 0.25200 0.13820 -1.21700 2.236e-01
## MI_ref10:CBT1:TIME_ref10 0.31470 0.34480 0.27670 1.13700 2.555e-01
## MI_ref10:CBT1:TIME_ref12 0.21090 0.35420 0.18190 1.15900 2.463e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_MIref1_TIMEref2) #ref: MI=1, CBT=0, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) 2.09200 0.13450 0.15150 13.8000 0.000000
## cAGE 0.11390 0.03201 0.04747 2.3990 0.016460
## MI_ref10 -0.22910 0.18810 0.20110 -1.1390 0.254600
## CBT1 -0.14460 0.17980 0.18720 -0.7724 0.439900
## TIME_ref20 0.35430 0.18400 0.13190 2.6870 0.007217
## TIME_ref21 -0.21100 0.18780 0.10700 -1.9730 0.048500
## MI_ref10:CBT1 0.16450 0.25350 0.26820 0.6133 0.539700
## MI_ref10:TIME_ref20 0.10670 0.25750 0.20830 0.5122 0.608500
## MI_ref10:TIME_ref21 0.21260 0.26180 0.13660 1.5560 0.119800
## CBT1:TIME_ref20 0.05211 0.24800 0.17440 0.2988 0.765100
## CBT1:TIME_ref21 0.16820 0.25200 0.13820 1.2170 0.223600
## MI_ref10:CBT1:TIME_ref20 0.10380 0.34880 0.27940 0.3714 0.710400
## MI_ref10:CBT1:TIME_ref21 -0.21090 0.35420 0.18190 -1.1590 0.246300
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_CBTref1) #ref: MI=0, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.4990 0.11430 0.10070 24.8100 0.000e+00
## cAGE 0.1139 0.03201 0.04747 2.3990 1.646e-02
## MI1 -0.1458 0.16270 0.13070 -1.1160 2.645e-01
## CBT_ref10 -0.1758 0.16860 0.15800 -1.1120 2.659e-01
## TIME1 -0.6581 0.16460 0.12740 -5.1660 2.400e-07
## TIME2 -0.6169 0.16640 0.14700 -4.1960 2.720e-05
## MI1:CBT_ref10 0.2682 0.24020 0.20320 1.3200 1.869e-01
## MI1:TIME1 0.2088 0.23350 0.17050 1.2250 2.206e-01
## MI1:TIME2 0.2104 0.23520 0.18620 1.1300 2.585e-01
## CBT_ref10:TIME1 0.1986 0.24180 0.21650 0.9173 3.590e-01
## CBT_ref10:TIME2 0.1559 0.24530 0.21830 0.7141 4.752e-01
## MI1:CBT_ref10:TIME1 -0.3147 0.34480 0.27670 -1.1370 2.555e-01
## MI1:CBT_ref10:TIME2 -0.1038 0.34880 0.27940 -0.3714 7.104e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.841000 0.11840 0.12660 14.54000 0.000e+00
## cAGE 0.113900 0.03201 0.04747 2.39900 1.646e-02
## MI1 0.062970 0.16750 0.17040 0.36940 7.118e-01
## CBT_ref10 0.022860 0.17380 0.19020 0.12020 9.043e-01
## TIME_ref10 0.658100 0.16460 0.12740 5.16600 2.400e-07
## TIME_ref12 0.041250 0.16930 0.08224 0.50150 6.160e-01
## MI1:CBT_ref10 -0.046410 0.24790 0.27500 -0.16880 8.660e-01
## MI1:TIME_ref10 -0.208800 0.23350 0.17050 -1.22500 2.206e-01
## MI1:TIME_ref12 0.001647 0.23850 0.12000 0.01373 9.890e-01
## CBT_ref10:TIME_ref10 -0.198600 0.24180 0.21650 -0.91730 3.590e-01
## CBT_ref10:TIME_ref12 -0.042750 0.24880 0.11850 -0.36090 7.182e-01
## MI1:CBT_ref10:TIME_ref10 0.314700 0.34480 0.27670 1.13700 2.555e-01
## MI1:CBT_ref10:TIME_ref12 0.210900 0.35420 0.18190 1.15900 2.463e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_CBTref1_TIMEref2) #ref: MI=0, CBT=1, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) 1.882000 0.12100 0.13630 13.81000 0.0000000
## cAGE 0.113900 0.03201 0.04747 2.39900 0.0164600
## MI1 0.064610 0.16990 0.17490 0.36940 0.7118000
## CBT_ref10 -0.019890 0.17850 0.19030 -0.10450 0.9168000
## TIME_ref20 0.616900 0.16640 0.14700 4.19600 0.0000272
## TIME_ref21 -0.041250 0.16930 0.08224 -0.50150 0.6160000
## MI1:CBT_ref10 0.164500 0.25350 0.26820 0.61330 0.5397000
## MI1:TIME_ref20 -0.210400 0.23520 0.18620 -1.13000 0.2585000
## MI1:TIME_ref21 -0.001647 0.23850 0.12000 -0.01373 0.9890000
## CBT_ref10:TIME_ref20 -0.155900 0.24530 0.21830 -0.71410 0.4752000
## CBT_ref10:TIME_ref21 0.042750 0.24880 0.11850 0.36090 0.7182000
## MI1:CBT_ref10:TIME_ref20 0.103800 0.34880 0.27940 0.37140 0.7104000
## MI1:CBT_ref10:TIME_ref21 -0.210900 0.35420 0.18190 -1.15900 0.2463000
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.35300 0.11590 0.08323 28.2800 0.000e+00
## cAGE 0.11390 0.03201 0.04747 2.3990 1.646e-02
## MI_ref10 0.14580 0.16270 0.13070 1.1160 2.645e-01
## CBT_ref10 0.09249 0.17090 0.12650 0.7310 4.648e-01
## TIME1 -0.44930 0.16570 0.11330 -3.9670 7.287e-05
## TIME2 -0.40640 0.16630 0.11440 -3.5540 3.800e-04
## MI_ref10:CBT_ref10 -0.26820 0.24020 0.20320 -1.3200 1.869e-01
## MI_ref10:TIME1 -0.20880 0.23350 0.17050 -1.2250 2.206e-01
## MI_ref10:TIME2 -0.21040 0.23520 0.18620 -1.1300 2.585e-01
## CBT_ref10:TIME1 -0.11600 0.24580 0.17210 -0.6741 5.002e-01
## CBT_ref10:TIME2 0.05211 0.24800 0.17440 0.2988 7.651e-01
## MI_ref10:CBT_ref10:TIME1 0.31470 0.34480 0.27670 1.1370 2.555e-01
## MI_ref10:CBT_ref10:TIME2 0.10380 0.34880 0.27940 0.3714 7.104e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.904000 0.11840 0.11420 16.68000 0.000e+00
## cAGE 0.113900 0.03201 0.04747 2.39900 1.646e-02
## MI_ref10 -0.062970 0.16750 0.17040 -0.36940 7.118e-01
## CBT_ref10 -0.023550 0.17670 0.19900 -0.11830 9.058e-01
## TIME_ref10 0.449300 0.16570 0.11330 3.96700 7.287e-05
## TIME_ref12 0.042900 0.16810 0.08743 0.49060 6.237e-01
## MI_ref10:CBT_ref10 0.046410 0.24790 0.27500 0.16880 8.660e-01
## MI_ref10:TIME_ref10 0.208800 0.23350 0.17050 1.22500 2.206e-01
## MI_ref10:TIME_ref12 -0.001647 0.23850 0.12000 -0.01373 9.890e-01
## CBT_ref10:TIME_ref10 0.116000 0.24580 0.17210 0.67410 5.002e-01
## CBT_ref10:TIME_ref12 0.168200 0.25200 0.13820 1.21700 2.236e-01
## MI_ref10:CBT_ref10:TIME_ref10 -0.314700 0.34480 0.27670 -1.13700 2.555e-01
## MI_ref10:CBT_ref10:TIME_ref12 -0.210900 0.35420 0.18190 -1.15900 2.463e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(ncigs_interaction_MIref1_CBTref1_TIMEref2) #ref: MI=1, CBT=1, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) 1.947000 0.11920 0.10970 17.74000 0.00000
## cAGE 0.113900 0.03201 0.04747 2.39900 0.01646
## MI_ref10 -0.064610 0.16990 0.17490 -0.36940 0.71180
## CBT_ref10 0.144600 0.17980 0.18720 0.77240 0.43990
## TIME_ref20 0.406400 0.16630 0.11440 3.55400 0.00038
## TIME_ref21 -0.042900 0.16810 0.08743 -0.49060 0.62370
## MI_ref10:CBT_ref10 -0.164500 0.25350 0.26820 -0.61330 0.53970
## MI_ref10:TIME_ref20 0.210400 0.23520 0.18620 1.13000 0.25850
## MI_ref10:TIME_ref21 0.001647 0.23850 0.12000 0.01373 0.98900
## CBT_ref10:TIME_ref20 -0.052110 0.24800 0.17440 -0.29880 0.76510
## CBT_ref10:TIME_ref21 -0.168200 0.25200 0.13820 -1.21700 0.22360
## MI_ref10:CBT_ref10:TIME_ref20 -0.103800 0.34880 0.27940 -0.37140 0.71040
## MI_ref10:CBT_ref10:TIME_ref21 0.210900 0.35420 0.18190 1.15900 0.24630
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.9902
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
# DV: SMDK ---------------------------
#relevel MI and CBT
SMDK_dt_na.omit$MI_ref1 <- SMDK_dt_na.omit$MI %>% relevel("1")
SMDK_dt_na.omit$CBT_ref1 <- SMDK_dt_na.omit$CBT %>% relevel("1")
SMDK_dt_na.omit$TIME_ref1 <- SMDK_dt_na.omit$TIME %>% relevel("1")
SMDK_dt_na.omit$TIME_ref2 <- SMDK_dt_na.omit$TIME %>% relevel("2")
## fit main model
SMDK_main <- geem(formula = SMDK.main,
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summary
summary(SMDK_main)
## Estimates Model SE Robust SE wald p
## (Intercept) -0.08744 0.02814 0.02599 -3.3650 0.0007657
## cAGE 0.02691 0.01136 0.01462 1.8410 0.0655900
## MI1 0.05722 0.02532 0.03208 1.7840 0.0744200
## CBT1 -0.03167 0.02537 0.03213 -0.9857 0.3243000
## TIME1 -0.20410 0.03059 0.02651 -7.7000 0.0000000
## TIME2 -0.18840 0.03088 0.02748 -6.8550 0.0000000
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1209
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
## fit interaction model
SMDK_interaction <- geem(formula = SMDK.interaction,
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_TIMEref1 <- geem(formula =
SMDK ~ cAGE + MI + CBT + TIME_ref1 + MI * CBT + MI * TIME_ref1 + CBT *
TIME_ref1 + MI * CBT * TIME_ref1 + offset(log_unctrldays),
#ref: Mi=0, Cbt=0, time=1
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_TIMEref2 <- geem(formula =
SMDK ~ cAGE + MI + CBT + TIME_ref2 + MI * CBT + MI * TIME_ref2 + CBT *
TIME_ref2 + MI * CBT * TIME_ref2 + offset(log_unctrldays),
#ref: Mi=0, Cbt=0, time=1
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_MIref1 <-
geem(formula = SMDK ~ cAGE + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 * TIME + CBT *
TIME + MI_ref1 * CBT * TIME + offset(log_unctrldays),
#ref: Mi=1, Cbt=0, time=0
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_MIref1_TIMEref1 <-
geem(formula = SMDK ~ cAGE + MI_ref1 + CBT + TIME_ref1 + MI_ref1 * CBT + MI_ref1 * TIME_ref1 + CBT *
TIME_ref1 + MI_ref1 * CBT * TIME_ref1 + offset(log_unctrldays),
#ref: Mi=1, Cbt=0, time=1
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_MIref1_TIMEref2 <-
geem(formula = SMDK ~ cAGE + MI_ref1 + CBT + TIME_ref2 + MI_ref1 * CBT + MI_ref1 * TIME_ref2 + CBT *
TIME_ref2 + MI_ref1 * CBT * TIME_ref2 + offset(log_unctrldays),
#ref: Mi=1, Cbt=0, time=2
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_CBTref1 <-
geem(formula = SMDK ~ cAGE + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI * TIME + CBT_ref1 *
TIME + MI * CBT_ref1 * TIME + offset(log_unctrldays),
#ref: Mi=0, Cbt=1, time=0
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_CBTref1_TIMEref1 <-
geem(formula = SMDK ~ cAGE + MI + CBT_ref1 + TIME_ref1 + MI * CBT_ref1 + MI * TIME_ref1 + CBT_ref1 *
TIME_ref1 + MI * CBT_ref1 * TIME_ref1 + offset(log_unctrldays),
#ref: Mi=0, Cbt=1, time=1
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_CBTref1_TIMEref2 <-
geem(formula = SMDK ~ cAGE + MI + CBT_ref1 + TIME_ref2 + MI * CBT_ref1 + MI * TIME_ref2 + CBT_ref1 *
TIME_ref2 + MI * CBT_ref1 * TIME_ref2 + offset(log_unctrldays),
#ref: Mi=0, Cbt=1, time=2
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_MIref1_CBTref1 <-
geem(formula = SMDK ~ cAGE + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 * TIME + CBT_ref1 *
TIME + MI_ref1 * CBT_ref1 * TIME + offset(log_unctrldays),
#ref: MI_ref1=1, Cbt=1, time=0
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = SMDK ~ cAGE + MI_ref1 + CBT_ref1 + TIME_ref1 + MI_ref1 * CBT_ref1 + MI_ref1 * TIME_ref1 + CBT_ref1 *
TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1 + offset(log_unctrldays),
#ref: MI_ref1=1, Cbt=1, time=1
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
SMDK_interaction_MIref1_CBTref1_TIMEref2 <-
geem(formula = SMDK ~ cAGE + MI_ref1 + CBT_ref1 + TIME_ref2 + MI_ref1 * CBT_ref1 + MI_ref1 * TIME_ref2 + CBT_ref1 *
TIME_ref2 + MI_ref1 * CBT_ref1 * TIME_ref2 + offset(log_unctrldays),
#ref: MI_ref1=1, Cbt=1, time=2
data = SMDK_dt_na.omit,
id=id,
family = MASS::negative.binomial(1)
)
## print interaction model summary
summary(SMDK_interaction) #ref: MI=0, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) -0.092470 0.04440 0.02272 -4.07000 4.696e-05
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI1 0.021000 0.06331 0.02753 0.76290 4.455e-01
## CBT1 0.022800 0.06040 0.02782 0.81950 4.125e-01
## TIME1 -0.208900 0.06370 0.05969 -3.49900 4.672e-04
## TIME2 -0.148400 0.06464 0.05593 -2.65300 7.978e-03
## MI1:CBT1 -0.026240 0.08605 0.03654 -0.71830 4.726e-01
## MI1:TIME1 0.028330 0.09122 0.07527 0.37630 7.067e-01
## MI1:TIME2 0.044790 0.09232 0.06750 0.66350 5.070e-01
## CBT1:TIME1 -0.018060 0.08686 0.07851 -0.23010 8.180e-01
## CBT1:TIME2 -0.195900 0.08801 0.08757 -2.23700 2.528e-02
## MI1:CBT1:TIME1 0.003268 0.12380 0.10530 0.03104 9.752e-01
## MI1:CBT1:TIME2 0.157400 0.12510 0.10710 1.47000 1.416e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_TIMEref1) #ref: MI=0, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) -0.301300 0.04583 0.05928 -5.08300 3.700e-07
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI1 0.049330 0.06592 0.07684 0.64200 5.209e-01
## CBT1 0.004735 0.06256 0.07880 0.06008 9.521e-01
## TIME_ref10 0.208900 0.06370 0.05969 3.49900 4.672e-04
## TIME_ref12 0.060480 0.06564 0.05059 1.19500 2.320e-01
## MI1:CBT1 -0.022980 0.08926 0.10610 -0.21650 8.286e-01
## MI1:TIME_ref10 -0.028330 0.09122 0.07527 -0.37630 7.067e-01
## MI1:TIME_ref12 0.016460 0.09417 0.06473 0.25430 7.992e-01
## CBT1:TIME_ref10 0.018060 0.08686 0.07851 0.23010 8.180e-01
## CBT1:TIME_ref12 -0.177800 0.08950 0.06960 -2.55500 1.062e-02
## MI1:CBT1:TIME_ref10 -0.003268 0.12380 0.10530 -0.03104 9.752e-01
## MI1:CBT1:TIME_ref12 0.154100 0.12730 0.09416 1.63700 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_TIMEref2) #ref: MI=0, CBT=0, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) -0.24080 0.04712 0.05465 -4.4070 1.046e-05
## cAGE 0.02781 0.01150 0.01494 1.8620 6.259e-02
## MI1 0.06579 0.06748 0.06710 0.9804 3.269e-01
## CBT1 -0.17310 0.06414 0.08734 -1.9820 4.749e-02
## TIME_ref20 0.14840 0.06464 0.05593 2.6530 7.978e-03
## TIME_ref21 -0.06048 0.06564 0.05059 -1.1950 2.320e-01
## MI1:CBT1 0.13110 0.09097 0.10620 1.2350 2.169e-01
## MI1:TIME_ref20 -0.04479 0.09232 0.06750 -0.6635 5.070e-01
## MI1:TIME_ref21 -0.01646 0.09417 0.06473 -0.2543 7.992e-01
## CBT1:TIME_ref20 0.19590 0.08801 0.08757 2.2370 2.528e-02
## CBT1:TIME_ref21 0.17780 0.08950 0.06960 2.5550 1.062e-02
## MI1:CBT1:TIME_ref20 -0.15740 0.12510 0.10710 -1.4700 1.416e-01
## MI1:CBT1:TIME_ref21 -0.15410 0.12730 0.09416 -1.6370 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_MIref1) #ref: MI=1, CBT=0, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) -0.071460 0.04502 0.01403 -5.09500 3.500e-07
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI_ref10 -0.021000 0.06331 0.02753 -0.76290 4.455e-01
## CBT1 -0.003446 0.06121 0.02253 -0.15290 8.785e-01
## TIME1 -0.180500 0.06530 0.04552 -3.96600 7.312e-05
## TIME2 -0.103600 0.06591 0.03789 -2.73400 6.262e-03
## MI_ref10:CBT1 0.026240 0.08605 0.03654 0.71830 4.726e-01
## MI_ref10:TIME1 -0.028330 0.09122 0.07527 -0.37630 7.067e-01
## MI_ref10:TIME2 -0.044790 0.09232 0.06750 -0.66350 5.070e-01
## CBT1:TIME1 -0.014790 0.08828 0.07007 -0.21110 8.328e-01
## CBT1:TIME2 -0.038500 0.08885 0.06165 -0.62460 5.323e-01
## MI_ref10:CBT1:TIME1 -0.003268 0.12380 0.10530 -0.03104 9.752e-01
## MI_ref10:CBT1:TIME2 -0.157400 0.12510 0.10710 -1.47000 1.416e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) -0.252000 0.04733 0.04879 -5.16500 2.400e-07
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI_ref10 -0.049330 0.06592 0.07684 -0.64200 5.209e-01
## CBT1 -0.018240 0.06363 0.07089 -0.25730 7.969e-01
## TIME_ref10 0.180500 0.06530 0.04552 3.96600 7.312e-05
## TIME_ref12 0.076940 0.06754 0.04027 1.91100 5.606e-02
## MI_ref10:CBT1 0.022980 0.08926 0.10610 0.21650 8.286e-01
## MI_ref10:TIME_ref10 0.028330 0.09122 0.07527 0.37630 7.067e-01
## MI_ref10:TIME_ref12 -0.016460 0.09417 0.06473 -0.25430 7.992e-01
## CBT1:TIME_ref10 0.014790 0.08828 0.07007 0.21110 8.328e-01
## CBT1:TIME_ref12 -0.023710 0.09055 0.06329 -0.37460 7.080e-01
## MI_ref10:CBT1:TIME_ref10 0.003268 0.12380 0.10530 0.03104 9.752e-01
## MI_ref10:CBT1:TIME_ref12 -0.154100 0.12730 0.09416 -1.63700 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_MIref1_TIMEref2) #ref: MI=1, CBT=0, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) -0.17510 0.04821 0.03866 -4.5290 5.940e-06
## cAGE 0.02781 0.01150 0.01494 1.8620 6.259e-02
## MI_ref10 -0.06579 0.06748 0.06710 -0.9804 3.269e-01
## CBT1 -0.04195 0.06444 0.05990 -0.7003 4.837e-01
## TIME_ref20 0.10360 0.06591 0.03789 2.7340 6.262e-03
## TIME_ref21 -0.07694 0.06754 0.04027 -1.9110 5.606e-02
## MI_ref10:CBT1 -0.13110 0.09097 0.10620 -1.2350 2.169e-01
## MI_ref10:TIME_ref20 0.04479 0.09232 0.06750 0.6635 5.070e-01
## MI_ref10:TIME_ref21 0.01646 0.09417 0.06473 0.2543 7.992e-01
## CBT1:TIME_ref20 0.03850 0.08885 0.06165 0.6246 5.323e-01
## CBT1:TIME_ref21 0.02371 0.09055 0.06329 0.3746 7.080e-01
## MI_ref10:CBT1:TIME_ref20 0.15740 0.12510 0.10710 1.4700 1.416e-01
## MI_ref10:CBT1:TIME_ref21 0.15410 0.12730 0.09416 1.6370 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_CBTref1) #ref: MI=0, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) -0.069670 0.04094 0.01557 -4.47500 7.630e-06
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI1 -0.005242 0.05827 0.02355 -0.22250 8.239e-01
## CBT_ref10 -0.022800 0.06040 0.02782 -0.81950 4.125e-01
## TIME1 -0.226900 0.05905 0.05119 -4.43300 9.300e-06
## TIME2 -0.344300 0.05973 0.06756 -5.09600 3.500e-07
## MI1:CBT_ref10 0.026240 0.08605 0.03654 0.71830 4.726e-01
## MI1:TIME1 0.031590 0.08376 0.07383 0.42790 6.687e-01
## MI1:TIME2 0.202200 0.08436 0.08318 2.43100 1.507e-02
## CBT_ref10:TIME1 0.018060 0.08686 0.07851 0.23010 8.180e-01
## CBT_ref10:TIME2 0.195900 0.08801 0.08757 2.23700 2.528e-02
## MI1:CBT_ref10:TIME1 -0.003268 0.12380 0.10530 -0.03104 9.752e-01
## MI1:CBT_ref10:TIME2 -0.157400 0.12510 0.10710 -1.47000 1.416e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) -0.296600 0.04255 0.05138 -5.77300 1.000e-08
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI1 0.026350 0.06017 0.07267 0.36260 7.169e-01
## CBT_ref10 -0.004735 0.06256 0.07880 -0.06008 9.521e-01
## TIME_ref10 0.226900 0.05905 0.05119 4.43300 9.300e-06
## TIME_ref12 -0.117400 0.06084 0.04781 -2.45500 1.410e-02
## MI1:CBT_ref10 0.022980 0.08926 0.10610 0.21650 8.286e-01
## MI1:TIME_ref10 -0.031590 0.08376 0.07383 -0.42790 6.687e-01
## MI1:TIME_ref12 0.170600 0.08568 0.06837 2.49500 1.259e-02
## CBT_ref10:TIME_ref10 -0.018060 0.08686 0.07851 -0.23010 8.180e-01
## CBT_ref10:TIME_ref12 0.177800 0.08950 0.06960 2.55500 1.062e-02
## MI1:CBT_ref10:TIME_ref10 0.003268 0.12380 0.10530 0.03104 9.752e-01
## MI1:CBT_ref10:TIME_ref12 -0.154100 0.12730 0.09416 -1.63700 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_CBTref1_TIMEref2) #ref: MI=0, CBT=1, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) -0.41390 0.04349 0.06757 -6.126 0.000e+00
## cAGE 0.02781 0.01150 0.01494 1.862 6.259e-02
## MI1 0.19690 0.06100 0.08161 2.413 1.582e-02
## CBT_ref10 0.17310 0.06414 0.08734 1.982 4.749e-02
## TIME_ref20 0.34430 0.05973 0.06756 5.096 3.500e-07
## TIME_ref21 0.11740 0.06084 0.04781 2.455 1.410e-02
## MI1:CBT_ref10 -0.13110 0.09097 0.10620 -1.235 2.169e-01
## MI1:TIME_ref20 -0.20220 0.08436 0.08318 -2.431 1.507e-02
## MI1:TIME_ref21 -0.17060 0.08568 0.06837 -2.495 1.259e-02
## CBT_ref10:TIME_ref20 -0.19590 0.08801 0.08757 -2.237 2.528e-02
## CBT_ref10:TIME_ref21 -0.17780 0.08950 0.06960 -2.555 1.062e-02
## MI1:CBT_ref10:TIME_ref20 0.15740 0.12510 0.10710 1.470 1.416e-01
## MI1:CBT_ref10:TIME_ref21 0.15410 0.12730 0.09416 1.637 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, time=0
## Estimates Model SE Robust SE wald p
## (Intercept) -0.074910 0.04146 0.01767 -4.24000 2.239e-05
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI_ref10 0.005242 0.05827 0.02355 0.22250 8.239e-01
## CBT_ref10 0.003446 0.06121 0.02253 0.15290 8.785e-01
## TIME1 -0.195300 0.05940 0.05326 -3.66700 2.453e-04
## TIME2 -0.142100 0.05958 0.04868 -2.91900 3.513e-03
## MI_ref10:CBT_ref10 -0.026240 0.08605 0.03654 -0.71830 4.726e-01
## MI_ref10:TIME1 -0.031590 0.08376 0.07383 -0.42790 6.687e-01
## MI_ref10:TIME2 -0.202200 0.08436 0.08318 -2.43100 1.507e-02
## CBT_ref10:TIME1 0.014790 0.08828 0.07007 0.21110 8.328e-01
## CBT_ref10:TIME2 0.038500 0.08885 0.06165 0.62460 5.323e-01
## MI_ref10:CBT_ref10:TIME1 0.003268 0.12380 0.10530 0.03104 9.752e-01
## MI_ref10:CBT_ref10:TIME2 0.157400 0.12510 0.10710 1.47000 1.416e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, time=1
## Estimates Model SE Robust SE wald p
## (Intercept) -0.270200 0.04254 0.05147 -5.25000 1.500e-07
## cAGE 0.027810 0.01150 0.01494 1.86200 6.259e-02
## MI_ref10 -0.026350 0.06017 0.07267 -0.36260 7.169e-01
## CBT_ref10 0.018240 0.06363 0.07089 0.25730 7.969e-01
## TIME_ref10 0.195300 0.05940 0.05326 3.66700 2.453e-04
## TIME_ref12 0.053230 0.06033 0.04888 1.08900 2.762e-01
## MI_ref10:CBT_ref10 -0.022980 0.08926 0.10610 -0.21650 8.286e-01
## MI_ref10:TIME_ref10 0.031590 0.08376 0.07383 0.42790 6.687e-01
## MI_ref10:TIME_ref12 -0.170600 0.08568 0.06837 -2.49500 1.259e-02
## CBT_ref10:TIME_ref10 -0.014790 0.08828 0.07007 -0.21110 8.328e-01
## CBT_ref10:TIME_ref12 0.023710 0.09055 0.06329 0.37460 7.080e-01
## MI_ref10:CBT_ref10:TIME_ref10 -0.003268 0.12380 0.10530 -0.03104 9.752e-01
## MI_ref10:CBT_ref10:TIME_ref12 0.154100 0.12730 0.09416 1.63700 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
summary(SMDK_interaction_MIref1_CBTref1_TIMEref2) #ref: MI=1, CBT=1, time=2
## Estimates Model SE Robust SE wald p
## (Intercept) -0.21700 0.04278 0.04596 -4.7220 2.340e-06
## cAGE 0.02781 0.01150 0.01494 1.8620 6.259e-02
## MI_ref10 -0.19690 0.06100 0.08161 -2.4130 1.582e-02
## CBT_ref10 0.04195 0.06444 0.05990 0.7003 4.837e-01
## TIME_ref20 0.14210 0.05958 0.04868 2.9190 3.513e-03
## TIME_ref21 -0.05323 0.06033 0.04888 -1.0890 2.762e-01
## MI_ref10:CBT_ref10 0.13110 0.09097 0.10620 1.2350 2.169e-01
## MI_ref10:TIME_ref20 0.20220 0.08436 0.08318 2.4310 1.507e-02
## MI_ref10:TIME_ref21 0.17060 0.08568 0.06837 2.4950 1.259e-02
## CBT_ref10:TIME_ref20 -0.03850 0.08885 0.06165 -0.6246 5.323e-01
## CBT_ref10:TIME_ref21 -0.02371 0.09055 0.06329 -0.3746 7.080e-01
## MI_ref10:CBT_ref10:TIME_ref20 -0.15740 0.12510 0.10710 -1.4700 1.416e-01
## MI_ref10:CBT_ref10:TIME_ref21 -0.15410 0.12730 0.09416 -1.6370 1.017e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 0.1229
##
## Number of GEE iterations: 2
## Number of Clusters: 278 Maximum Cluster Size: 3
## Number of observations with nonzero weight: 791
# DV = LONGABS ---------------------------
## fit main model
#relevel MI and CBT
LONGABS_nobl_dt$MI_ref1 <- LONGABS_nobl_dt$MI %>% relevel("1")
LONGABS_nobl_dt$CBT_ref1 <- LONGABS_nobl_dt$CBT %>% relevel("1")
LONGABS_nobl_dt$TIME_ref1 <- LONGABS_nobl_dt$TIME %>% relevel("1")
CLONGABS_nobl_main <- geem(formula =
CLONGABS ~ cAGE + cBLCGSMD + MI + CBT + TIME,
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summary
summary(CLONGABS_nobl_main) #unlogged
## Estimates Model SE Robust SE wald p
## (Intercept) 1.710000 0.20750 0.22290 7.67300 0.000000
## cAGE -0.130200 0.09316 0.11490 -1.13300 0.257200
## cBLCGSMD -0.001452 0.01168 0.01595 -0.09105 0.927500
## MI1 -0.748200 0.20370 0.24840 -3.01200 0.002599
## CBT1 0.692700 0.20510 0.24750 2.79800 0.005135
## TIME1 0.008417 0.20280 0.13420 0.06270 0.950000
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.816
##
## Number of GEE iterations: 3
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
## fit interaction models
CLONGABS_nobl_interaction <- geem(formula = CLONGABS.nobl.interaction,
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print interaction models' summary
summary(CLONGABS_nobl_interaction) #unlogged
## Estimates Model SE Robust SE wald p
## (Intercept) -1.94000 0.26250 0.2233 -8.6880 0.0000
## cAGE -0.12350 0.08254 0.1451 -0.8514 0.3945
## cBLCGSMD -0.03319 0.01003 0.0395 -0.8403 0.4007
## MI1 -0.54300 0.39020 0.3564 -1.5240 0.1276
## CBT1 0.25260 0.35260 0.3218 0.7851 0.4324
## TIME1 -0.03922 0.37340 0.2055 -0.1908 0.8486
## MI1:CBT1 0.41830 0.51530 0.4710 0.8881 0.3745
## MI1:TIME1 -0.58830 0.57090 0.4344 -1.3540 0.1756
## CBT1:TIME1 0.29280 0.49970 0.2599 1.1270 0.2598
## MI1:CBT1:TIME1 0.07867 0.74520 0.5274 0.1492 0.8814
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 3.479
##
## Number of GEE iterations: 9
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
# DV = LONGABS ---------------------------
# #relevel MI and CBT
LONGABS_nobl_dt$MI_ref1 <- LONGABS_nobl_dt$MI %>% relevel("1")
LONGABS_nobl_dt$CBT_ref1 <- LONGABS_nobl_dt$CBT %>% relevel("1")
LONGABS_nobl_dt$TIME_ref1 <- LONGABS_nobl_dt$TIME %>% relevel("1")
## main model
LONGABS_nobl_main <- geem(formula = CLONGABS.nobl.main,
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print main model summary
summary(LONGABS_nobl_main)
## Estimates Model SE Robust SE wald p
## (Intercept) -1.983000 0.17630 0.21210 -9.3500 0.00000
## cAGE -0.188300 0.07857 0.10100 -1.8640 0.06238
## cBLCGSMD -0.009257 0.01004 0.01623 -0.5705 0.56830
## MI1 -0.660400 0.17400 0.21870 -3.0200 0.00253
## CBT1 0.638000 0.17580 0.22000 2.9000 0.00373
## TIME1 -0.115800 0.17330 0.12700 -0.9118 0.36190
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 3.148
##
## Number of GEE iterations: 9
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
## interaction model
LONGABS_nobl_interaction <- geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI + CBT + TIME + MI * CBT + MI * TIME +
CBT * TIME + MI * CBT * TIME,
#mi=0, cbt=0, time=0
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_TIMEref1 <- geem(formula =
CLONGABS ~ cAGE + cBLCGSMD + MI + CBT + TIME_ref1 + MI * CBT + MI * TIME_ref1 +
CBT * TIME_ref1 + MI * CBT * TIME_ref1,
#mi=0, cbt=0, time=1
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_MIref1 <-
geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME + MI_ref1 * CBT + MI_ref1 * TIME +
CBT * TIME + MI_ref1 * CBT * TIME,
#ref: Mi=1, Cbt=0, Time=0
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_MIref1_TIMEref1 <-
geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT + TIME_ref1 +
MI_ref1 * CBT + MI_ref1 * TIME_ref1 +
CBT * TIME_ref1 + MI_ref1 * CBT * TIME_ref1,
#ref: Mi=1, Cbt=0, Time=1
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_CBTref1 <-
geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME + MI * CBT_ref1 + MI *
TIME + CBT_ref1 * TIME + MI * CBT_ref1 * TIME,
#ref: Mi=0, Cbt=1, Time = 0
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_CBTref1_TIMEref1 <-
geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI + CBT_ref1 + TIME_ref1 +
MI * CBT_ref1 + MI * TIME_ref1 + CBT_ref1 * TIME_ref1 + MI * CBT_ref1 * TIME_ref1,
#ref: Mi=0, Cbt=1, Time = 1
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_MIref1_CBTref1 <-
geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME + MI_ref1 * CBT_ref1 + MI_ref1 *
TIME + CBT_ref1 * TIME + MI_ref1 * CBT_ref1 * TIME,
#ref: Mi=1, Cbt=1, Time=0
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
LONGABS_nobl_interaction_MIref1_CBTref1_TIMEref1 <-
geem(formula = CLONGABS ~ cAGE + cBLCGSMD + MI_ref1 + CBT_ref1 + TIME_ref1 +
MI_ref1 * CBT_ref1 + MI_ref1 * TIME_ref1 +
CBT_ref1 * TIME_ref1 + MI_ref1 * CBT_ref1 * TIME_ref1,
#ref: Mi=1, Cbt=1, Time=1
data = LONGABS_nobl_dt,
id=id,
family = MASS::negative.binomial(1)
)
## print interaction model summary
summary(LONGABS_nobl_interaction) #base: MI=0, CBT=0, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.6520000 0.29880 0.25290 6.53200 0.00000
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.19500
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.96440
## MI1 -0.5704000 0.43700 0.37950 -1.50300 0.13280
## CBT1 0.5529000 0.40100 0.31830 1.73700 0.08243
## TIME1 0.2183000 0.41700 0.26400 0.82670 0.40840
## MI1:CBT1 0.1861000 0.57940 0.52240 0.35630 0.72160
## MI1:TIME1 -0.6656000 0.62790 0.48010 -1.38600 0.16560
## CBT1:TIME1 0.0476600 0.56180 0.31130 0.15310 0.87830
## MI1:CBT1:TIME1 0.2107000 0.82790 0.58470 0.36040 0.71860
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_TIMEref1) #base: MI=0, CBT=0, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.8700000 0.29400 0.31000 6.03200 0.00000
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.19500
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.96440
## MI1 -1.2360000 0.45380 0.53310 -2.31900 0.02042
## CBT1 0.6005000 0.39630 0.35660 1.68400 0.09221
## TIME_ref10 -0.2183000 0.41700 0.26400 -0.82670 0.40840
## MI1:CBT1 0.3968000 0.59460 0.66450 0.59720 0.55040
## MI1:TIME_ref10 0.6656000 0.62790 0.48010 1.38600 0.16560
## CBT1:TIME_ref10 -0.0476600 0.56180 0.31130 -0.15310 0.87830
## MI1:CBT1:TIME_ref10 -0.2107000 0.82790 0.58470 -0.36040 0.71860
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_MIref1) #ref: MI=1, CBT=0, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.0820000 0.31850 0.27930 3.87300 0.0001076
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.1950000
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.9644000
## MI_ref10 0.5704000 0.43700 0.37950 1.50300 0.1328000
## CBT1 0.7390000 0.41750 0.41090 1.79900 0.0720700
## TIME1 -0.4474000 0.46940 0.40120 -1.11500 0.2649000
## MI_ref10:CBT1 -0.1861000 0.57940 0.52240 -0.35630 0.7216000
## MI_ref10:TIME1 0.6656000 0.62790 0.48010 1.38600 0.1656000
## CBT1:TIME1 0.2584000 0.60820 0.49600 0.52080 0.6025000
## MI_ref10:CBT1:TIME1 -0.2107000 0.82790 0.58470 -0.36040 0.7186000
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_MIref1_TIMEref1) #ref: MI=1, CBT=0, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 0.6342000 0.34550 0.41690 1.52100 0.12820
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.19500
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.96440
## MI_ref10 1.2360000 0.45380 0.53310 2.31900 0.02042
## CBT1 0.9974000 0.44250 0.55080 1.81100 0.07019
## TIME_ref10 0.4474000 0.46940 0.40120 1.11500 0.26490
## MI_ref10:CBT1 -0.3968000 0.59460 0.66450 -0.59720 0.55040
## MI_ref10:TIME_ref10 -0.6656000 0.62790 0.48010 -1.38600 0.16560
## CBT1:TIME_ref10 -0.2584000 0.60820 0.49600 -0.52080 0.60250
## MI_ref10:CBT1:TIME_ref10 0.2107000 0.82790 0.58470 0.36040 0.71860
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_CBTref1) #ref: MI=0, CBT=1, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 2.2050000 0.26690 0.19380 11.38000 0.00000
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.19500
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.96440
## MI1 -0.3843000 0.37990 0.35170 -1.09300 0.27460
## CBT_ref10 -0.5529000 0.40100 0.31830 -1.73700 0.08243
## TIME1 0.2659000 0.37640 0.16570 1.60500 0.10860
## MI1:CBT_ref10 -0.1861000 0.57940 0.52240 -0.35630 0.72160
## MI1:TIME1 -0.4549000 0.53960 0.33330 -1.36500 0.17230
## CBT_ref10:TIME1 -0.0476600 0.56180 0.31130 -0.15310 0.87830
## MI1:CBT_ref10:TIME1 -0.2107000 0.82790 0.58470 -0.36040 0.71860
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_CBTref1_TIMEref1) #ref: MI=0, CBT=1, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 2.4710000 0.26540 0.17750 13.92000 0.00000
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.19500
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.96440
## MI1 -0.8392000 0.38380 0.38880 -2.15900 0.03088
## CBT_ref10 -0.6005000 0.39630 0.35660 -1.68400 0.09221
## TIME_ref10 -0.2659000 0.37640 0.16570 -1.60500 0.10860
## MI1:CBT_ref10 -0.3968000 0.59460 0.66450 -0.59720 0.55040
## MI1:TIME_ref10 0.4549000 0.53960 0.33330 1.36500 0.17230
## CBT_ref10:TIME_ref10 0.0476600 0.56180 0.31130 0.15310 0.87830
## MI1:CBT_ref10:TIME_ref10 0.2107000 0.82790 0.58470 0.36040 0.71860
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_MIref1_CBTref1) #ref: MI=1, CBT=1, Time=0
## Estimates Model SE Robust SE wald p
## (Intercept) 1.8210000 0.27020 0.29380 6.19600 0.00000
## cAGE -0.1498000 0.09382 0.11560 -1.29600 0.19500
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 0.96440
## MI_ref10 0.3843000 0.37990 0.35170 1.09300 0.27460
## CBT_ref10 -0.7390000 0.41750 0.41090 -1.79900 0.07207
## TIME1 -0.1890000 0.38670 0.28970 -0.65240 0.51410
## MI_ref10:CBT_ref10 0.1861000 0.57940 0.52240 0.35630 0.72160
## MI_ref10:TIME1 0.4549000 0.53960 0.33330 1.36500 0.17230
## CBT_ref10:TIME1 -0.2584000 0.60820 0.49600 -0.52080 0.60250
## MI_ref10:CBT_ref10:TIME1 0.2107000 0.82790 0.58470 0.36040 0.71860
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
summary(LONGABS_nobl_interaction_MIref1_CBTref1_TIMEref1) #ref: MI=1, CBT=1, Time=1
## Estimates Model SE Robust SE wald p
## (Intercept) 1.6320000 0.27690 0.34850 4.68200 2.840e-06
## cAGE -0.1498000 0.09382 0.11560 -1.29600 1.950e-01
## cBLCGSMD 0.0006783 0.01175 0.01518 0.04469 9.644e-01
## MI_ref10 0.8392000 0.38380 0.38880 2.15900 3.088e-02
## CBT_ref10 -0.9974000 0.44250 0.55080 -1.81100 7.019e-02
## TIME_ref10 0.1890000 0.38670 0.28970 0.65240 5.141e-01
## MI_ref10:CBT_ref10 0.3968000 0.59460 0.66450 0.59720 5.504e-01
## MI_ref10:TIME_ref10 -0.4549000 0.53960 0.33330 -1.36500 1.723e-01
## CBT_ref10:TIME_ref10 0.2584000 0.60820 0.49600 0.52080 6.025e-01
## MI_ref10:CBT_ref10:TIME_ref10 -0.2107000 0.82790 0.58470 -0.36040 7.186e-01
##
## Estimated Correlation Parameter: 0
## Correlation Structure: independence
## Est. Scale Parameter: 4.841
##
## Number of GEE iterations: 4
## Number of Clusters: 282 Maximum Cluster Size: 2
## Number of observations with nonzero weight: 560
# Save ---------------------------
save.image(file="gee-main-interaction-models.RData")