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From | omer@demog.berkeley.edu |
To | statalist@hsphsun2.harvard.edu |
Subject | st: ?Test? command for continuous variables? |
Date | Thu, 9 Jan 2014 04:21:59 -0000 |
Hello, STATA listservers. I was hoping you could help me out with a statistical issue I have that I?m trying to resolve before sending a revised paper to a social science journal. Thanks so much in advance for your help. In one part of my analysis my dependent variables are levels of various biomarkers (cortisol, DHEAS, dopamine, and others) analyzed individually. My independent variables of interest are two measures of subjective social status. Each measure asks respondents to rate their social status on a ladder that has 10 rungs. One of the ladders asks respondents to rate themselves in terms of where they think they stand nationally (taking into account their level of education, income, and job type), and the other asks them to rate themselves where they think they stand relative to their community (taking into account whatever factors they feel are important to them). In Model A I include just the SES ladder as the key independent variable with a number of baseline controls (Model 1). I then keep the SES ladder in the model but add objective measures of status (i.e. educational levels and occupation prestige score) (Model 2). The idea here is to see whether the subjective SES ladder predicts riskier biomarker profiles net of objective indicators of status. In Model B I then do the same set of analyses (Model 1 and 2), but using only the subjective community ladder. In Model C I include both status ladders in Model 1 and 2. In Model C I also perform an F-test using Stata (i.e. after the regression I type ?test subjective_SES_ladder subjective_community_ladder?). One of my big questions is whether using the ?test? command in Stata is appropriate here. I have read that it is only appropriate with categorical variables, but I?m not sure if this is the case. If it is only appropriate for categorical variables, why does Stata even produce results for these two continuous variables? Another issue has to do with the correlation of the ladders. The two ladder measures are highly correlated (with a Pearson correlation, equal to the Spearman rank correlation, of 0.78), but respondents ranked their social position within their community an average of 0.4-rung higher than they ranked their position within Taiwan. One reviewer wondered why we present results from the two ladders since analysis of both ladders ?are far from independent analyses.? My thinking was that even if the ladders are highly correlated, they may very well tap very different phenomenon. I also thought that you never know if one will turn out to be more linked to riskier biomarkers profiles than other. I also thought that maybe in a test of joint significance both ladders would together be significant even if each on their own wasn?t. Does this thinking make sense? If this does not make sense, one option is to present results from one ladder and say that the results for either ladder were nearly the same. If I use this approach, results stemming from which ladder should I present? Perhaps I should present results for the community ladder because respondents ranked themselves higher in terms of the community, suggesting that their standing in the community is more relevant to them. Also, I sort of like the community ladder question better because it has no prompts. Thanks, Omer ------------------------------------------------------------ Omer Gersten, PhD * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/