The Stata help is somewhat confusing as to how variables are treated. Note that computation is based on an iterative procedure and therefore may take a few minutes if a large number of correlations is requested. Will compute the requested polychoric correlations.
Will inform you how to download the procedure (you need Stata 8.2 or higher for the procedure to work). The polychoric correlation is not included as a standard procedure in Stata. In this case the polychoric correlation is a good approximation of the correlation of the underlying continuous properties. Ordinal variables (like the usual Likert scaled attitude items) can also be considered as expression of an underlying continuous attribute. This can be obtained via the V option for crosstabulation (V is for Cramer's V, which in the case of a 2 x 2 table is equivalent to phi). Note that a few other options are available.Ī traditional measure for association of binary variables is phi, a chi-square based statistic that is numerically equivalent to Pearson's r. If only two variables are on the variables list, the stats option can be omitted, because all necessary information will be displayed by default. Will compute the tetrachoric correlations, their standard errors, the number of observations and the p-value, using pairwise deletion. Tetrachoric t1 t2 t3, pw stats(rho se obs p) One possibility to deal with binary variables is to see them as a resulting from an underlying continuous variable, with respondents below a certain cut-off point responding with "0" (or whatever the lower value may be) and those at or above the cut-off responding with "1" (or, more generally, the higher category. Again, any combination of these options is possible. lower), and star(.05) requests Stata to display a star with each correlation that is significant at. The option p(.1) tells Stata to display only correlations with a significance level of. Will display the number of observations for each correlation and the level of significance. Will display the covariance matrix instead of the correlation matrix. Will display mean, standard deviation, minimum and maximum of each variable. In contrast, "pwcorr" uses pairwise deletion in other words, each correlation is computed for all cases that do not have missing values for this specific pair of variables.Īnother difference are the options associated with each command. That is, the correlation matrix is computed only for those cases which do not have any missing value in any of the variables on the list. The first one is that with "corr", Stata uses listwise deletion. There are two kinds of difference between both commands. Will both do the same thing – display the matrix of correlations between variables f17 to f25 and f27. WLM Stata - Correlation Internet Guide to Stata