Below is the outcome without svyset and svy
Code:
. tabout x symptom if state==1 using table2B.xls, replace nwt(weight) nlab(Number) sebnone h1(nil) clab(freq 95%_CI) f(1 1) stats(chi2) Table output written to: table2B.xls x 0 1 Total Number freq freq freq 1 6884.0 922.0 7806.0 7,518 2 4443.0 479.0 4922.0 6,017 Total 11327.0 1401.0 12728.0 13,534 Pearson chi2(1) = 13.3273 Pr = 0.000
Code:
svyset [iw=weight] Importance weights: weight VCE: linearized Single unit: missing Strata 1: <one> Sampling unit 1: <observations> FPC 1: <zero> . tabout x symptom if state==1 using table2B.xls, replace svy nwt(weight) nlab(Number) sebnone h1(nil) clab(freq 95%_CI) f(1 1) stats(chi2) Survey results being calculated ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 ....... Table output written to: table2B.xls x 0 1 8 Total Number freq freq freq freq 1 6788.6 729.3 0.0 7517.9 7,791 2 5515.6 500.9 0.0 6016.5 4,920 3 0.0 0.0 0.0 0.0 0 Total 12304.2 1230.2 0.0 13534.4 12,711 Pearson: Uncorrected chi2(4) = . Design-based F(., .) = . Pr = .
How can I get it to estimate chisquare with the svyset and svy option.
Attached is the data. sampledata.dta
Thanks.
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