**1) Context**

Analysing PIAAC-Data via Logistic Regression

```
# 3.1) Multiple Logistic Regressions
# ---------------------- Germany -------------------------
# Literacy
table(sdf_deu_rebinded$LitLevel) # LitLevel 1 (Low): N=100, LitLevel 2 (Average): N=1371, LitLevel 3 (High): N=71
# a) Logistic Regression with LitAve as outcome-/success-level and LitLow as reference-level
# including Covariates and Predictors
logit_deu_Lit_ExHigh <- logit.sdf(
I(LitLevel == 2) ~ ageg10lfs + gender_r + nativelang + readytolearn_wle_ca + pared + edlevel3 + j_q02a + j_q03a,
data=sdf_deu_rebinded_EX_LitHigh,
weightVar = NULL,
relevels = list(j_q02a = "NO", j_q03a = "NO"),
varMethod = c("jackknife"),
jrrIMax = Inf,
omittedLevels = TRUE,
recode = NULL,
returnNumberOfPSU = FALSE,
returnVarEstInputs = TRUE
)
summary(logit_deu_Lit_ExHigh)
```

**2) Aims**

Export Results of Logistic Regression as Table (to use in Word)

**3) Problem and considered alternatives**

Attempted using edSurveyTable and finalfit-package

```
es1t <- edsurveyTable(glm(
I(LitLevel == 2) ~ ageg10lfs + gender_r + nativelang + readytolearn_wle_ca + pared + edlevel3 + j_q02a + j_q03a,
family = binomial(link = "logit"),
data=sdf_deu_rebinded_EX_LitHigh))
es1t <- edsurveyTable2pdf(glm(
I(LitLevel == 2) ~ ageg10lfs + gender_r + nativelang + readytolearn_wle_ca + pared + edlevel3 + j_q02a + j_q03a,
family = binomial(link = "logit"),
data=sdf_deu_rebinded_EX_LitHigh))
library(finalfit)
library(dplyr)
# Table 1
explanatory = c("ageg10lfs" + "gender_r", "nativelang", "readytolearn_wle_ca", "pared", "edlevel3", "j_q02a", "j_q03a")
dependent = I(LitLevel == 2)
colon_s %>%
finalfit(dependent, explanatory)
```