suppressPackageStartupMessages(library(tidyverse))
library(lme4)
library(Hmisc)Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Attaching package: 㤼㸱Hmisc㤼㸲
The following objects are masked from 㤼㸱package:dplyr㤼㸲:
src, summarize
The following objects are masked from 㤼㸱package:base㤼㸲:
format.pval, unitsglimpse(readprof)
Rows: 6,528
Columns: 8
$ schcode <dbl> 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 1...
$ lowses <dbl+lbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
$ female <dbl+lbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
$ minor <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
$ schcomp <dbl> -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2....
$ smallsch <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
$ id <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, ...
$ readprof <dbl> 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, ...`
readprof.2 <- readprof %>%
mutate(.,
lowses.fac = as_factor(lowses),
female.fac = as_factor(female),
minor.fac = as_factor(minor),
smallsch.fac = as_factor(smallsch),
readprof.fac = as_factor(readprof)
)
glimpse(readprof.2)Rows: 6,528
Columns: 13
$ schcode <dbl> 100, 100, 100, 100, 100, 100, 100, 100, 100, 10...
$ lowses <dbl+lbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
$ female <dbl+lbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
$ minor <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
$ schcomp <dbl> -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4,...
$ smallsch <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
$ id <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, ...
$ readprof <dbl> 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1,...
$ lowses.fac <fct> non-low socioeconomic status, non-low socioecon...
$ female.fac <fct> male, male, male, male, male, male, male, male,...
$ minor.fac <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
$ smallsch.fac <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
$ readprof.fac <fct> 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1,...model.null <- glmer(readprof.fac ~ (1|schcode), family = binomial, data = readprof.2)
summary(model.null)Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula: readprof.fac ~ (1 | schcode)
Data: readprof.2
AIC BIC logLik deviance df.resid
8868.5 8882.1 -4432.3 8864.5 6526
Scaled residuals:
Min 1Q Median 3Q Max
-1.7663 -0.9815 0.6879 0.9145 1.3931
Random effects:
Groups Name Variance Std.Dev.
schcode (Intercept) 0.2283 0.4778
Number of obs: 6528, groups: schcode, 122
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.13155 0.05198 2.531 0.0114 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1ICC.null <- 0.2283/ (0.2283+ (pi^2/3))
ICC.null[1] 0.06489173table(readprof.2$readprof.fac)
0 1
3066 3462 table(readprof.2$readprof)
0 1
3066 3462 model.2 <- glmer(readprof.fac ~ lowses.fac + female.fac + minor.fac + (1|schcode), family = binomial, data = readprof.2)
summary(model.2)Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula:
readprof.fac ~ lowses.fac + female.fac + minor.fac + (1 | schcode)
Data: readprof.2
AIC BIC logLik deviance df.resid
8696.8 8730.7 -4343.4 8686.8 6523
Scaled residuals:
Min 1Q Median 3Q Max
-1.9203 -0.9482 0.6194 0.8937 1.6114
Random effects:
Groups Name Variance Std.Dev.
schcode (Intercept) 0.1033 0.3214
Number of obs: 6528, groups: schcode, 122
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.39009 0.05876 6.639 3.15e-11
lowses.faclow socioeconomic status -0.43685 0.05717 -7.642 2.14e-14
female.facfemale 0.32357 0.05168 6.260 3.84e-10
minor.fac1 -0.43906 0.05605 -7.833 4.77e-15
(Intercept) ***
lowses.faclow socioeconomic status ***
female.facfemale ***
minor.fac1 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) lws.ss fml.fc
lwss.fclwss -0.359
femal.fcfml -0.415 -0.031
minor.fac1 -0.393 -0.171 -0.004ses.odds.ratio
[1] 0.64606831-0.6460683[1] 0.3539317female.odds.ratio <- exp(0.32357)
female.odds.ratio[1] 1.382053minor.odds.ratio <- exp(-0.43906)
minor.odds.ratio[1] 0.6446421model.3 <- glmer(readprof.fac ~ lowses.fac + female.fac + minor.fac + smallsch.fac + (1|schcode), family = binomial, data = readprof.2)
summary(model.3)Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula:
readprof.fac ~ lowses.fac + female.fac + minor.fac + smallsch.fac +
(1 | schcode)
Data: readprof.2
AIC BIC logLik deviance df.resid
8695.8 8736.5 -4341.9 8683.8 6522
Scaled residuals:
Min 1Q Median 3Q Max
-1.9364 -0.9556 0.6210 0.8947 1.6222
Random effects:
Groups Name Variance Std.Dev.
schcode (Intercept) 0.09668 0.3109
Number of obs: 6528, groups: schcode, 122
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.32449 0.07001 4.635 3.57e-06
lowses.faclow socioeconomic status -0.43920 0.05713 -7.688 1.50e-14
female.facfemale 0.32292 0.05167 6.249 4.12e-10
minor.fac1 -0.43983 0.05598 -7.857 3.94e-15
smallsch.fac1 0.13854 0.07941 1.745 0.0811
(Intercept) ***
lowses.faclow socioeconomic status ***
female.facfemale ***
minor.fac1 ***
smallsch.fac1 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) lws.ss fml.fc mnr.f1
lwss.fclwss -0.303
femal.fcfml -0.346 -0.031
minor.fac1 -0.336 -0.172 -0.003
smllsch.fc1 -0.552 -0.002 -0.003 0.009smallsch.odds.ratio
[1] 1.148596model.4 <- glmer(readprof.fac ~ lowses.fac + female.fac + minor.fac + smallsch.fac + schcomp + (1|schcode), family = binomial, data = readprof.2)
summary(model.4)Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula:
readprof.fac ~ lowses.fac + female.fac + minor.fac + smallsch.fac +
schcomp + (1 | schcode)
Data: readprof.2
AIC BIC logLik deviance df.resid
8665.5 8713.0 -4325.8 8651.5 6521
Scaled residuals:
Min 1Q Median 3Q Max
-2.0503 -0.9646 0.6064 0.8824 1.6455
Random effects:
Groups Name Variance Std.Dev.
schcode (Intercept) 0.05658 0.2379
Number of obs: 6528, groups: schcode, 122
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.28348 0.06401 4.429 9.48e-06
lowses.faclow socioeconomic status -0.36153 0.05778 -6.257 3.92e-10
female.facfemale 0.32237 0.05161 6.246 4.21e-10
minor.fac1 -0.39549 0.05580 -7.087 1.37e-12
smallsch.fac1 0.10372 0.07008 1.480 0.139
schcomp -0.20725 0.03511 -5.902 3.59e-09
(Intercept) ***
lowses.faclow socioeconomic status ***
female.facfemale ***
minor.fac1 ***
smallsch.fac1
schcomp ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) lws.ss fml.fc mnr.f1 smll.1
lwss.fclwss -0.329
femal.fcfml -0.377 -0.031
minor.fac1 -0.366 -0.159 -0.004
smllsch.fc1 -0.500 -0.024 -0.005 -0.002
schcomp 0.154 -0.278 -0.011 -0.175 0.083schcomp.odds.ratio <- exp(-0.20725)
schcomp.odds.ratio[1] 0.8128164#logit for male, low ses, minority
logit.1 <- 0.39009 + (-0.43685)+ (-0.43906)
logit.1[1] -0.48582#probability for male, low ses, minority
exp(logit.1)/(1+exp(logit.1))[1] 0.3808788#logit for female, not low ses, not minority
logit.2 <- 0.39009 + 0.32357
logit.2[1] 0.71366#probability for female, not low ses, not minority
exp(logit.2)/(1+exp(logit.2))[1] 0.6712094``
`
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