Hi,
I am relatively new to stata and I have a few related questions. I want to get proportion of units that answered a question( variable name = psysymps) by thier gender(sex) and race (race3cat) after I survey set the data. I tried "bysort race3cat: tab psysymps sex, row col chi2" but then realized the percentages were off and I needed to use svy commands. I then tried "svy: tab racet3cat sex, tab (psysymps) row se ci" but got a response that the table contains 0 in the marginals and therefore statsitics cannot be computed. I realized that one of the race categories (e.g. White) was not asked the question. So I created a new race category ("blackethn) that sets Whites to missing and others to either 1 or 2. Then I proceeded with my primary objective to see proportions of 'psysymps' by race and sex and tried "svy: tab blackethn sex, tab (psysymps) row se ci". This gave me the table below.
My questions are: 1) must I always svy set before each code e.g svy: tab instead of just tab?; 2) was it okay to set Whites to missing as they were not asked this question and I dont want them counted as a denominator in my proportion?; 3) the table below still does not give me tabs of my variable by race and sex. how do I do this? Instead the table gave me---of those who answered yes to psysymps, what proportion of race/blackethn =1 were men and what prop were women? I would like to know how to code to get----what proportion of race/blackethn==1 men answered 'yes' to psysymps, compared to race/blackethn== 1 female (and also the proportion of race/blackethn ==2 men that answered yes to to psysymps, compared to race/blackethn== 2 female and associated chi2)
Number of strata = 41 Number of obs = 5191
Number of PSUs = 88 Population size = 3061.3339
Design df = 47
-------------------------------------------------------
| rs sex
blackethn | male female Total
----------+--------------------------------------------
1 | .4019 .5981 1
| (.0248) (.0248)
| [.3532,.4526] [.5474,.6468]
|
2 | .5338 .4662 1
| (.0579) (.0579)
| [.4176,.6465] [.3535,.5824]
|
Total | .4101 .5899 1
| (.0235) (.0235)
| [.3638,.4581] [.5419,.6362]
-------------------------------------------------------
Tabulated variable: psysymps
Key: row proportions
(linearized standard errors of row proportions)
[95% confidence intervals for row proportions]
Pearson:
Uncorrected chi2(1) = 21.8483
Design-based F(1, 47) = 4.6397 P = 0.0364
Thanks so much in advance for your time
Adebola Odunlami, MPH
Doctoral Student
Society, Human Development and Health
Harvard School of Public Health
301 256 4655
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