Multilevel models Probl
m0 <- lmer(probl~1+(1|v2.idmen/id), data=alldat)
print(icc(m0, by_group = TRUE))## # ICC by Group
##
## Group | ICC
## -------------------
## id:v2.idmen | 0.041
## v2.idmen | 0.277m1 <- lmer(probl~relevel(cluster, ref="companionship")+sex+factor(wave)+length+(1|v2.idmen/id), data=alldat)
#m1b <- lmer(probl~relevel(cluster, ref="companionship")+sex+factor(wave)+factor(wave)*length+(1|v2.idmen/id), data=alldat)
#m1c <- lmer(probl~relevel(cluster, ref="companionship")+relevel(cluster, ref="companionship")*sex+factor(wave)+length+(1|v2.idmen/id), data=alldat)
m2 <- lmer(probl~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ+(1|v2.idmen/id), data=alldat)
#fm1 <- plm(probl~relevel(cluster, ref="companionship")+sex+factor(wave), index="id", model="within", data=alldat)
#fm2 <- plm(probl~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ, index="id", model="within", data=alldat)
#htmlreg(list("Multilevel 0"=m0, "Multilevel 1"=m1, "Multilevel 1b"=m1b,"Multilevel 1c"=m1c, "Multilevel 2"=m2, "Fixed-Effect 1"=fm1, "Fixed-Effect 2"=fm2))
htmlreg(list("Multilevel 0"=m0, "Multilevel 1"=m1, "Multilevel 2"=m2))| Multilevel 0 | Multilevel 1 | Multilevel 2 | |
|---|---|---|---|
| (Intercept) | 1.60*** | 1.16** | 0.58 |
| (0.07) | (0.38) | (0.44) | |
| relevel(cluster, ref = “companionship”)cocoon | 0.31 | 0.37 | |
| (0.35) | (0.36) | ||
| relevel(cluster, ref = “companionship”)bastion | 0.49 | 0.55 | |
| (0.38) | (0.39) | ||
| relevel(cluster, ref = “companionship”)association | 0.43*** | 0.39** | |
| (0.13) | (0.13) | ||
| relevel(cluster, ref = “companionship”)parallel | 0.58*** | 0.52*** | |
| (0.14) | (0.15) | ||
| sexh | -0.33*** | -0.43*** | |
| (0.08) | (0.11) | ||
| factor(wave)2 | 1.36*** | 1.43*** | |
| (0.34) | (0.35) | ||
| factor(wave)3 | 1.31*** | 1.40*** | |
| (0.34) | (0.35) | ||
| length | -0.03*** | -0.03*** | |
| (0.01) | (0.01) | ||
| educprof_school | 0.03 | ||
| (0.11) | |||
| educuniversity | 0.11 | ||
| (0.15) | |||
| enfenfants_oui | 0.45* | ||
| (0.21) | |||
| activ25-75% | 0.08 | ||
| (0.12) | |||
| activ>=80% | 0.20 | ||
| (0.12) | |||
| activretired | -0.05 | ||
| (0.19) | |||
| AIC | 8713.47 | 8466.00 | 8381.13 |
| BIC | 8735.99 | 8533.55 | 8482.21 |
| Log Likelihood | -4352.74 | -4221.00 | -4172.56 |
| Num. obs. | 2058 | 2058 | 2030 |
| Num. groups: id:v2.idmen | 686 | 686 | 686 |
| Num. groups: v2.idmen | 343 | 343 | 343 |
| Var: id:v2.idmen (Intercept) | 0.19 | 0.31 | 0.33 |
| Var: v2.idmen (Intercept) | 1.28 | 1.17 | 1.18 |
| Var: Residual | 3.15 | 2.65 | 2.65 |
| ***p < 0.001; **p < 0.01; *p < 0.05 | |||
Multilevel models satisf
m0 <- lmer(satisf~1+(1|v2.idmen/id), data=alldat)
print(icc(m0, by_group = TRUE))## # ICC by Group
##
## Group | ICC
## -------------------
## id:v2.idmen | 0.088
## v2.idmen | 0.310m0g <- glmer(satisf~1+(1|v2.idmen/id), data=alldat, family=binomial, control = glmerControl(optimizer = "bobyqa"))
print(icc(m0g, by_group = TRUE))## # ICC by Group
##
## Group | ICC
## -------------------
## id:v2.idmen | 0.061
## v2.idmen | 0.438#m1 <- lmer(satisf~relevel(cluster, ref="companionship")+sex+factor(wave)+length+(1|v2.idmen/id), data=alldat)
#m1b <- lmer(satisf~relevel(cluster, ref="companionship")+sex+factor(wave)+factor(wave)*length+(1|v2.idmen/id), data=alldat)
#m1c <- lmer(satisf~relevel(cluster, ref="companionship")+relevel(cluster, ref="companionship")*sex+factor(wave)+length+(1|v2.idmen/id), data=alldat)
#m2 <- lmer(satisf~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ+(1|v2.idmen/id), data=alldat)
m1g <- glmer(satisf~relevel(cluster, ref="companionship")+sex+factor(wave)+length+(1|v2.idmen/id), data=alldat, family=binomial, control = glmerControl(optimizer = "bobyqa",
optCtrl = list(maxfun=100000)))
m2g <- glmer(satisf~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ+(1|v2.idmen/id),
data=alldat, family=binomial, control = glmerControl(optimizer = "bobyqa",
optCtrl = list(maxfun=100000)))
#fm1 <- plm(satisf~relevel(cluster, ref="companionship")+sex+factor(wave), index="id", model="within", data=alldat)
#fm2 <- plm(satisf~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ, index="id", model="within", data=alldat)
#htmlreg(list("Multilevel 0"=m0, "Multilevel 1"=m1, "Multilevel 1b"=m1b,"Multilevel 1c"=m1c, "Multilevel 2"=m2, "Fixed-Effect 1"=fm1, "Fixed-Effect 2"=fm2, "Logistic 0"=m0g, "Logistic 1"=m1g, "Logistic 2"=m2g))
htmlreg(list("Multilevel 0"=m0, "Logistic 0"=m0g, "Logistic 1"=m1g, "Logistic 2"=m2g))| Multilevel 0 | Logistic 0 | Logistic 1 | Logistic 2 | |
|---|---|---|---|---|
| (Intercept) | 0.52*** | 0.10 | 0.51 | -0.13 |
| (0.02) | (0.11) | (0.58) | (0.65) | |
| relevel(cluster, ref = “companionship”)cocoon | -0.23 | -0.22 | ||
| (0.53) | (0.54) | |||
| relevel(cluster, ref = “companionship”)bastion | -0.58 | -0.48 | ||
| (0.57) | (0.58) | |||
| relevel(cluster, ref = “companionship”)association | 0.40* | 0.32 | ||
| (0.19) | (0.19) | |||
| relevel(cluster, ref = “companionship”)parallel | 0.39 | 0.34 | ||
| (0.22) | (0.22) | |||
| sexh | -0.29* | -0.26 | ||
| (0.12) | (0.15) | |||
| factor(wave)2 | -0.26 | -0.21 | ||
| (0.52) | (0.52) | |||
| factor(wave)3 | -0.15 | -0.17 | ||
| (0.51) | (0.53) | |||
| length | -0.01 | -0.01 | ||
| (0.01) | (0.01) | |||
| educprof_school | -0.19 | |||
| (0.16) | ||||
| educuniversity | -0.08 | |||
| (0.21) | ||||
| enfenfants_oui | 0.57 | |||
| (0.31) | ||||
| activ25-75% | 0.25 | |||
| (0.18) | ||||
| activ>=80% | 0.26 | |||
| (0.18) | ||||
| activretired | 0.52 | |||
| (0.28) | ||||
| AIC | 2598.46 | 2504.63 | 2501.99 | 2474.99 |
| BIC | 2620.97 | 2521.52 | 2563.91 | 2570.46 |
| Log Likelihood | -1295.23 | -1249.32 | -1240.00 | -1220.49 |
| Num. obs. | 2057 | 2057 | 2057 | 2030 |
| Num. groups: id:v2.idmen | 686 | 686 | 686 | 686 |
| Num. groups: v2.idmen | 343 | 343 | 343 | 343 |
| Var: id:v2.idmen (Intercept) | 0.02 | 0.40 | 0.38 | 0.38 |
| Var: v2.idmen (Intercept) | 0.08 | 2.88 | 2.76 | 2.77 |
| Var: Residual | 0.15 | |||
| ***p < 0.001; **p < 0.01; *p < 0.05 | ||||
Multilevel models sep
m0 <- lmer(sep~1+(1|v2.idmen/id), data=alldat)
print(icc(m0, by_group = TRUE))## # ICC by Group
##
## Group | ICC
## -------------------
## id:v2.idmen | 0.163
## v2.idmen | 0.309m0g <- glmer(sep~1+(1|v2.idmen/id), data=alldat, family=binomial, control = glmerControl(optimizer = "bobyqa"))
print(icc(m0g, by_group = TRUE))## # ICC by Group
##
## Group | ICC
## -------------------
## id:v2.idmen | 0.169
## v2.idmen | 0.483#m1 <- lmer(sep~relevel(cluster, ref="companionship")+sex+factor(wave)+length+(1|v2.idmen/id), data=alldat)
#m1b <- lmer(sep~relevel(cluster, ref="companionship")+sex+factor(wave)+factor(wave)*length+(1|v2.idmen/id), data=alldat)
#m1c <- lmer(sep~relevel(cluster, ref="companionship")+relevel(cluster, ref="companionship")*sex+factor(wave)+length+(1|v2.idmen/id), data=alldat)
#m2 <- lmer(sep~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ+(1|v2.idmen/id), data=alldat)
m1g <- glmer(sep~relevel(cluster, ref="companionship")+sex+factor(wave)+length+(1|v2.idmen/id), data=alldat, family=binomial, control = glmerControl(optimizer = "bobyqa",
optCtrl = list(maxfun=100000)))
m2g <- glmer(sep~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ+(1|v2.idmen/id),
data=alldat, family=binomial, control = glmerControl(optimizer = "bobyqa",
optCtrl = list(maxfun=100000)))
#fm1 <- plm(sep~relevel(cluster, ref="companionship")+sex+factor(wave), index="id", model="within", data=alldat)
#fm2 <- plm(sep~relevel(cluster, ref="companionship")+sex+factor(wave)+length+educ+enf+activ, index="id", model="within", data=alldat)
#htmlreg(list("Multilevel 0"=m0, "Multilevel 1"=m1, "Multilevel 1b"=m1b,"Multilevel 1c"=m1c, "Multilevel 2"=m2, "Fixed-Effect 1"=fm1, "Fixed-Effect 2"=fm2, "Logistic 0"=m0g, "Logistic 1"=m1g, "Logistic 2"=m2g))
htmlreg(list("Multilevel 0"=m0, "Logistic 0"=m0g, "Logistic 1"=m1g, "Logistic 2"=m2g))| Multilevel 0 | Logistic 0 | Logistic 1 | Logistic 2 | |
|---|---|---|---|---|
| (Intercept) | 0.26*** | -2.05*** | -1.04 | -2.41** |
| (0.02) | (0.19) | (0.69) | (0.82) | |
| relevel(cluster, ref = “companionship”)cocoon | -0.11 | -0.23 | ||
| (0.60) | (0.62) | |||
| relevel(cluster, ref = “companionship”)bastion | -0.70 | -0.74 | ||
| (0.70) | (0.73) | |||
| relevel(cluster, ref = “companionship”)association | 0.56* | 0.49* | ||
| (0.24) | (0.24) | |||
| relevel(cluster, ref = “companionship”)parallel | 0.42 | 0.39 | ||
| (0.27) | (0.27) | |||
| sexh | -0.96*** | -1.06*** | ||
| (0.17) | (0.22) | |||
| factor(wave)2 | -0.14 | -0.10 | ||
| (0.58) | (0.60) | |||
| factor(wave)3 | -0.05 | 0.06 | ||
| (0.58) | (0.60) | |||
| length | -0.03 | -0.02 | ||
| (0.02) | (0.02) | |||
| educprof_school | 0.09 | |||
| (0.21) | ||||
| educuniversity | 0.49 | |||
| (0.29) | ||||
| enfenfants_oui | 0.67 | |||
| (0.43) | ||||
| activ25-75% | 0.80*** | |||
| (0.24) | ||||
| activ>=80% | 0.72** | |||
| (0.24) | ||||
| activretired | 0.20 | |||
| (0.36) | ||||
| AIC | 1968.98 | 1978.34 | 1946.87 | 1912.96 |
| BIC | 1991.50 | 1995.23 | 2008.78 | 2008.42 |
| Log Likelihood | -980.49 | -986.17 | -962.43 | -939.48 |
| Num. obs. | 2056 | 2056 | 2056 | 2029 |
| Num. groups: id:v2.idmen | 686 | 686 | 686 | 686 |
| Num. groups: v2.idmen | 343 | 343 | 343 | 343 |
| Var: id:v2.idmen (Intercept) | 0.03 | 1.60 | 1.15 | 1.22 |
| Var: v2.idmen (Intercept) | 0.06 | 4.58 | 4.57 | 4.69 |
| Var: Residual | 0.10 | |||
| ***p < 0.001; **p < 0.01; *p < 0.05 | ||||
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