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| From | "John Morton" <john.morton@optusnet.com.au> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | st: Date: Wed, 22 Sep 2010 08:37:30 +1000 |
| Date | Tue, 21 Sep 2010 18:37:34 -0400 (EDT) |
Hi, I am seeking advice on analysis of a time series dataset in Stata. The same site was visited irregularly 30 times over 3 years (median interval between visits 35 days, range 18 to 68 days). At each visit, usually 5 tadpoles (but sometimes 6 or 9) were sampled (numbers were limited because this is an endangered species). Different tadpoles were sampled at each visit. Each tadpole was tested and categorised as test positive or test negative. Apparent prevalences were 1.00 at about half of the visits and 0.00 at about 25% of visits. The researcher?s question is whether prevalence varies by month (ie Jan, Feb, Mar etc) or by season. The features of this data that seem important are that the errors would be expected to be serially correlation over time, the dependent variable is binary, prevalences of 0 and 1 were common, the very small number of tadpoles sampled at each visit, and these are not panel data (ie different tadpoles were sampled at each visit). I have done some exploratory modelling treating prevalence as a continuous dependent variable (using -regress-) after declaring the data to be time-series data (with sequential visit number rather than day number as the time variable, using -tsset-). With a null model, tests for serial correlation (Durbin-Watson test (-estat dwatson-), Durbin?s alternative (h) test (-estat durbinalt-),Breush-Godfrey test ( -estat bgodfrey,lag(6)-), Portmaneau (Q) test (-wntestq-) and the autocorrelogram (-ac-)(all from Baum 2006) indicate serial correlation. In contrast, after fitting month as a fixed effect, these tests do not support rejecting the null hypothesis that no serial correlation exists. However treating prevalence (a proportion) as a continuous dependent variable (using -regress-) is inappropriate. Any suggestions on approaches to answer the research question would be much appreciated. Many thanks for any help. John *************************************************************** Dr John Morton BVSc (Hons) PhD MACVSc (Veterinary Epidemiology) Veterinary Epidemiological Consultant Jemora Pty Ltd PO Box 2277 Geelong 3220 Victoria Australia Ph: +61 (0)3 52 982 082 Mob: 0407 092 558 Email: john.morton@optusnet.com.au *************************************************************** * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/