调查加权 t 检验未显示 r 中均值的正确差异?
survey weighted t test not showing correct difference in mean in r?
我正在使用 R 中的复杂调查数据进行分析。但是,当我使用调查包中的 svyttest 来执行设计基础 t 检验时,它没有提供正确的均值差异
svyby(~preds,~SDDSRVYR,svymean, design=subset(data, age==2))
SDDSRVYR preds se
7 7 0.2340050 0.01161363
10 10 0.3159294 0.01076532
tt<-svyttest(preds~SDDSRVYR, design=subset(data, age==2))
> tt
Design-based t-test
data: preds ~ SDDSRVYR
t = 5.1734, df = 30, p-value = 1.428e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
0.01696236 0.03765392
sample estimates:
difference in mean
0.02730814
如您所见,均值差异约为 0.082,但 t 检验显示其为 0.03。我不明白 t 检验是如何计算均值的吗?我无法想象它与 svymean 有什么不同...或者这可能是一个编码问题?
我发现答案-SDDSRVYR 被视为连续的(它取值 7 和 10)。不是二进制
svyttest(preds~factor(SDDSRVYR), design=subset(data, age==2))
Design-based t-test
data: preds ~ factor(SDDSRVYR)
t = 5.1734, df = 30, p-value = 1.428e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
0.05088707 0.11296176
sample estimates:
difference in mean
0.08192442
我正在使用 R 中的复杂调查数据进行分析。但是,当我使用调查包中的 svyttest 来执行设计基础 t 检验时,它没有提供正确的均值差异
svyby(~preds,~SDDSRVYR,svymean, design=subset(data, age==2))
SDDSRVYR preds se
7 7 0.2340050 0.01161363
10 10 0.3159294 0.01076532
tt<-svyttest(preds~SDDSRVYR, design=subset(data, age==2))
> tt
Design-based t-test
data: preds ~ SDDSRVYR
t = 5.1734, df = 30, p-value = 1.428e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
0.01696236 0.03765392
sample estimates:
difference in mean
0.02730814
如您所见,均值差异约为 0.082,但 t 检验显示其为 0.03。我不明白 t 检验是如何计算均值的吗?我无法想象它与 svymean 有什么不同...或者这可能是一个编码问题?
我发现答案-SDDSRVYR 被视为连续的(它取值 7 和 10)。不是二进制
svyttest(preds~factor(SDDSRVYR), design=subset(data, age==2))
Design-based t-test
data: preds ~ factor(SDDSRVYR)
t = 5.1734, df = 30, p-value = 1.428e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
0.05088707 0.11296176
sample estimates:
difference in mean
0.08192442