具有多种选择和权重变量的交叉表

Question

我正在学习使用出色的“ expss” R包。

我需要知道是否可以使用此程序包在多选变量和分类变量之间建立列联表，考虑权重变量

在此数据框中，类别变量为“性”，权重变量为“ survey_weight”：

demo <- tribble(
~dummy1, ~dummy2, ~dummy3, ~survey_weight, ~sex,
      1,       0,       0,          1.5,  "male",
      1,       1,       0,          1.5,  "female",
      1,       1,       1,           .5,  "female",
      0,       1,       1,          1.5,  "male",
      1,       1,       1,           .5,  "male",
      0,       0,       1,           .5,  "male",
)
demo 

我需要根据回答问题的总受访者而不是总答复来计算百分比。

提前感谢！

Answer 1

library(expss)
demo = text_to_columns('
 dummy1   dummy2   dummy3  survey_weight  sex
      1        0        0            1.5  male
      1        1        0            1.5  female
      1        1        1             .5  female
      0        1        1            1.5  male
      1        1        1             .5  male
      0        0        1             .5  male
')


demo %>% 
    tab_cells(mdset(dummy1 %to% dummy3)) %>%  # 'mdset' designate that with have multiple dichotomy set
    tab_cols(sex) %>%  # columns
    tab_weight(survey_weight) %>% # weight
    tab_stat_cpct() %>% # statistic
    tab_pivot() 

# |              |    sex |      |
# |              | female | male |
# | ------------ | ------ | ---- |
# |       dummy1 |    100 | 50.0 |
# |       dummy2 |    100 | 50.0 |
# |       dummy3 |     25 | 62.5 |
# | #Total cases |      2 |  4.0 |

# shorter notation with the same result
calc_cro_cpct(demo, mdset(dummy1 %to% dummy3), sex, weight = survey_weight)

Answer 2

也许我们可以使用cro_cpct

library(expss)
calculate(demo, cro_cpct(list(dummy1, dummy2, dummy3), weight = survey_weight, sex))
#                                 
# |              |    sex |      |
# |              | female | male |
# | ------------ | ------ | ---- |
# |            0 |        | 50.0 |
# |            1 |    100 | 50.0 |
# | #Total cases |      2 |  4.0 |
# |            0 |        | 50.0 |
# |            1 |    100 | 50.0 |
# | #Total cases |      2 |  4.0 |
# |            0 |     75 | 37.5 |
# |            1 |     25 | 62.5 |
# | #Total cases |      2 |  4.0 |