如何使用R调查软件包分析加权样本中的多个回答问题？

Question

我对R比较新。我想知道如何使用“调查”包（http://r-survey.r-forge.r-project.org/survey/）来分析加权样本的多重回答问题？棘手的是，可以勾选多个响应，以便将响应存储在多个列中。

例子：

我有500名受访者谁是随机来自全国10个地区得出的调查数据。假设被问到的主要问题是（存储在H1_AreYouHappy列中）：'你快乐吗？' - 是/否/不知道

被访者被问到后续问题：'你为什么（快乐）？ 这是一个选择题，可以选择多个答案框，因此答案被存储在单独的列中，例如：

H1Yes_Why1（0/1，即选择框打勾或未打勾） - '因为economny“;

H1Yes_Why2（0/1） - '因为我健康';

H1Yes_Why3（0/1） - '因为我的社交生活'。

下面是根据各地区

library(survey) 
# Create an unweighted survey object 
mySurvey.unweighted <- svydesign(ids=~1, data=myDataFrame) 

# Choose which variable contains the sample distribution to be weighted by 
sample.distribution <- list(~District) 

# Specify (from Census data) how often each level occurs in the population 
population.distribution <- data.frame(District = c('Green', 'Red','Orange','Blue','Purple','Grey','Black','Yellow','White','Lavender'), 
           freq = c(0.1824885, 0.0891206, 0.1381343, 0.1006533, 0.1541269, 0.0955853, 0.0268172, 0.0398353, 0.0809459, 0.0922927)) 

# Apply the weights 
mySurvey.rake <- rake(design = mySurvey.unweighted, sample.margins=sample.distribution, population.margins=list(population.distribution)) 

# Calculate the weighted mean for the main question 
svymean(~H1_AreYouHappy, mySurvey.rake) 

# How can I calculate the WEIGHTED means for the multiple choice - multiple response follow-up question? 

的事实上的人口规模我的假数据集

districts <- c('Green', 'Red','Orange','Blue','Purple','Grey','Black','Yellow','White','Lavender') 
myDataFrame <- data.frame(H1_AreYouHappy=sample(c('Yes','No','Dont Know'),500,rep=TRUE), 
          H1Yes_Why1 = sample(0:1,500,rep=TRUE), 
          H1Yes_Why2 = sample(0:1,500,rep=TRUE), 
          H1Yes_Why3 = sample(0:1,500,rep=TRUE), 
          District = sample(districts,500,rep=TRUE), stringsAsFactors=TRUE) 

我使用的R“调查”包申请后分层权重我如何计算多项选择问题的加权平均值（即跨越0/1响应列）？

如果我想它不加权的，我可以使用此功能横跨符合我的前缀“H1Yes_Why”

multipleResponseFrequencies = function(data, question.prefix) { 
    # Find the columns with the questions 
    a = grep(question.prefix, names(data)) 
    # Find the total number of responses 
    b = sum(data[, a] != 0) 
    # Find the totals for each question 
    d = colSums(data[, a] != 0) 
    # Find the number of respondents 
    e = sum(rowSums(data[,a]) !=0) 
    # d + b as a vector. This is the overfall frequency 
    f = as.numeric(c(d, b)) 
    result <- data.frame(question = c(names(d), "Total"), 
         freq = f, 
         percent = (f/b)*100, 
         percentofcases = (f/e)*100) 
    result 
} 
multipleResponseFrequencies(myDataFrame, 'H1Yes_Why') 

任何帮助，将不胜感激所有列计算的频率。

Answer 1

我想你想

svyratio(~ H1Yes_Why1 + H1Yes_Why2 + H1Yes_Why3 , ~ as.numeric(H1Yes_Why1 + H1Yes_Why2 + H1Yes_Why3) , mySurvey.rake)