David Winsemius <[EMAIL PROTECTED]> wrote in news:[EMAIL PROTECTED]:
> raymond chiruka <[EMAIL PROTECTED]> wrote in > news:[EMAIL PROTECTED]: > >> i am trying to carry out a categorical data analysis but my problem >> is that when in i use the chi squared test some of my expected >> values are less than 5. is there a test that can handle this >> situation. the data is not a 2*2 table. its more from the social >> sciences where you have from strongly agree to strongly disagree. i >> know i can collapse vthe tables but there is a loss of information . >> is the a test vthat i can for this kind of data. thanks in advancde. > > In addition to Snow's suggestion of fisher.test, you may want to look > more closely at: > ?chisq.test snip Another possibility for the analysis of ordered catergorical response might be proportional odds regression. The MASS package has polr: library(MASS) ?polr ------------ polr(formula, data, weights, start, ..., subset, na.action, contrasts = NULL, Hess = FALSE, model = TRUE, method = c("logistic", "probit", "cloglog", "cauchit")) Arguments formula: a formula expression as for regression models, of the form response ~ predictors. The response should be a factor (preferably an ordered factor), which will be interpreted as an ordinal response, with levels ordered as in the factor. ----------------- My copy of Venables&Ripley's MASS is an older version and neither the index nor the TOC tells me where to find worked examples. Harrell's Regression Modeling Strategies has a case study illustrating the use of his lrm function. So you might also look at: library(Design) ?lrm -- David Winsemius ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
