Dear Impute listserv members:
We have a survey instrument called the Canadian COmmunity Health Survey
(CCHS-similar to the national health interview survey in the United States).
We are using the survey to study the interaction between aging, religiousity,
and health services utilization.
The problem we are having is that the first wave of the survey in 2001
(the only wave appropriate for our questions) has a sample size of
approximately 133,000 but the module on religiousity was only given to a
random subset of approximately 3,000. We feel that we have some good
predictors of church attendance in some of our behavioral variables such as
smoking and alcohol consumption; however, Wilcoxon tests of our imputations
with the distributions of the actual values from the sample subset force us to
reject the hypothesis that they are from the same distribution.
The same question on religiousity was also used in a second wave of the
survey instrument in late 2001 in which all 37,000 in the second wave were
asked the question we are interested in. Unfortunately, the dependent
variables were not available in this wave. What is useful here in that the
distribution of responses to the question of interest (frequency of church
attendance) is statistically not different than the distribution for the same
question in the first wave (according to the results of the Wilcoxon text).
Given this information, can you suggest anything we might try which might
have a shot at imputing values for such a large percentage of a sample and
offer a test of accuracy of the imputation other than the Wilcoxon test?
Any help you can provide will be much appreciated.
--
Eric Nauenberg, Ph.D.
Associate Professor of Health Economics
Department of Health Policy, Management and Evaluation
Faculty of Medicine, University of Toronto
Health Sciences Building
155 College Street Suite 425
Toronto, ON Canada M5T 3M6
(416) 212-6109
----- End forwarded message -----
--
Eric Nauenberg, Ph.D.
Associate Professor of Health Economics
Department of Health Policy, Management and Evaluation
Faculty of Medicine, University of Toronto
Health Sciences Building
155 College Street Suite 425
Toronto, ON Canada M5T 3M6
(416) 212-6109
----- End forwarded message -----
--
Eric Nauenberg, Ph.D.
Associate Professor of Health Economics
Department of Health Policy, Management and Evaluation
Faculty of Medicine, University of Toronto
Health Sciences Building
155 College Street Suite 425
Toronto, ON Canada M5T 3M6
(416) 212-6109
