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I am using stby in summary tools to calculated weighted descriptive statistics by group. However, when I do this I am getting a different answer compared to when I filter by grouping variable and then apply the descr function in summary tools. See below - mydf = my unfiltered dataframe, score is a 0-10 variable that I want to get the mean of.
##when I filter first and split my df
filtered_male <- mydf$gender %>% filter(gender==1)
with(filtered_male, stby(score, gender, descr, weights = weight))
Weighted Descriptive Statistics
score by gender
Data Frame: filtered_male
Weights: weight
N: 838
1
Mean 6.86
Std.Dev 2.93
Min 0.00
Median 8.00
Max 10.00
MAD 2.97
CV 0.43
N.Valid 1509584.07
Pct.Valid 99.70
##when I don't split my df
with(mydf, stby(score, gender, descr, weights = weight, simplify = TRUE))
Weighted Descriptive Statistics
score by gender
Data Frame: mydf
Weights: weight
N: 838
1 2
Mean 7.01 6.79
Std.Dev 2.81 3.02
Min 0.00 0.00
Median 8.00 8.00
Max 10.00 10.00
MAD 2.97 2.97
CV 0.40 0.45
N.Valid 1715494.12 1379339.65
Pct.Valid 56.05 45.07
'''
Any idea's on why this is happening or how I fix it to get the correct weighted mean? (I've check the answers manually and the mean where I filter first is correct). Also, this doesn't seem to be an issue when I don't use weights.
The text was updated successfully, but these errors were encountered:
I am using stby in summary tools to calculated weighted descriptive statistics by group. However, when I do this I am getting a different answer compared to when I filter by grouping variable and then apply the descr function in summary tools. See below - mydf = my unfiltered dataframe, score is a 0-10 variable that I want to get the mean of.
##when I filter first and split my df
filtered_male <- mydf$gender %>% filter(gender==1)
with(filtered_male, stby(score, gender, descr, weights = weight))
Weighted Descriptive Statistics
score by gender
Data Frame: filtered_male
Weights: weight
N: 838
##when I don't split my df
with(mydf, stby(score, gender, descr, weights = weight, simplify = TRUE))
Weighted Descriptive Statistics
score by gender
Data Frame: mydf
Weights: weight
N: 838
'''
Any idea's on why this is happening or how I fix it to get the correct weighted mean? (I've check the answers manually and the mean where I filter first is correct). Also, this doesn't seem to be an issue when I don't use weights.
The text was updated successfully, but these errors were encountered: