I need help with the tasks and can't get any further with writing code. Can you help me?
Install and load packages
load("minaret.RDa")
head(minaret)
summary(minaret)
library(survey)
library(graphics)
library(dplyr)
library(tidyverse)
- Think about ways to group the cantons into fewer (say, 2 to 7) politico-culturally homogeneous regions (note that there is no one correct solution here). Explain your choice.
In this step, I define three regions that are politically and culturally homogeneous. I can do this on the basis of geographical proximity and cultural similarities. In this case, I have chosen the following regions:
Region 1: Zurich, Bern, Basel-Stadt, Aargau, Solothurn, Lucerne
Region 2: GraubĂĽnden, St. Gallen, Thurgau, Schaffhausen, Appenzell Innerrhoden, Appenzell Ausserrhoden
Region 3: Valais, Ticino, Unterwalden, Jura, Neuchâtel, Vaud
region_map <- data.frame(
canton_id = c(1:20),
region_id = c(rep("Region 1", 6), rep("Region 2", 8), rep("Region 3", 6))
)
- Recode
canton_id
into a new variableregion_id
according to your scheme. Sort minaret frame byregion_id
(this is a necessary for the sampling functions to work properly!)
2. Recode canton_id into region_id
minaret_region <- merge(minaret, region_map, by = "canton_id")
minaret_region <- arrange(minaret_region, region_id)
3. Use `region_id` as a stratification variable. Draw a sample of size $n=1000$, allocate the sample to the strata proportional to their size (look up the code in our previous Rmd file on Sampling).
```{r, message=FALSE}
set.seed(123) # Set seed for reproducibility
sample_size <- 1000
sample_data <- minaret %>%
group_by(region_id) %>%
sample_n(size = floor(prop.table(table(region_id)) * sample_size))
# Display the first few rows of the stratified sample
head(sample_data)
Error in group_by()
:
! Must group by variables found in .data
.
Column region_id
is not found.
Backtrace:
-
minaret %>% group_by(region_id) %>% ...
-
dplyr:::group_by.data.frame(., region_id)
Fehler in group_by(., region_id) :
Columnregion_id
is not found. -
Specify a
svydesign
object -
Estimate the population share of yes votes in the initiative.
-
Estimate the design effect, interpret the design effect in terms of the effective sample size.