Re: Analysis of a time series of categorical data
On 3 May 2001 09:46:12 -0700, [EMAIL PROTECTED] (R. Mark Sharp; Ext. 476) wrote: If there is a better venue for this question, please advise me. - an epidemiology mailing list? [ snip, much detail ] Time point 1Time point 2Time point 3Time point 4 Hosts Inf Not-InfInf Not-InfInf Not-InfInf Not-Inf Tested G1-S11 14 11 4 11 1 13 2 57 G1-S27 8 12 3 14 2 15 8 69 G1-S31 246 18815915 95 G2-S43 12 12 4 10 4 14 2 61 G2-S55 105 68 7 1114 57 G2-S62 26 12 12 1116 1412 105 The questions are how can group 1 (G1) be compare to group 2 (G2) and how can subgroups be compared. I maintain that the heterogeneity within each group does not prevent pooling of the subgroup data within each group, because the groupings were made a priori based on genetic similarity. Mostly, heterogeneity prevents pooling. What's an average supposed to mean? Only if the Ns represent naturally-occurring proportions, and so does your hypothesis, then you MIGHT want to analyze the numbers that way. How much do you know about the speed of expected onset, and offset of the disease? If this were real, It looks to me like you would want special software. Or special evaluation of a likelihood function. I can put the hypothesis in simple ANOVA terms, comparing species (S). Then, the within-Variability of G1 and G2 -- which is big -- would be used to test the difference Between: according to some parameter. Would that be an estimate of maximum number afflicted? -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Analysis of a time series of categorical data
If there is a better venue for this question, please advise me. I am looking for methods to analyze categorical data similar to that shown below. If the results were quantitative, I believe that an analysis of covariance would be appropriate. However, with categorical data and relatively small samples, I am at a loss. Any help would be appreciated. The purpose of the experiment was to discover whether or not two groups of infectious organisms differ in there ability to infect a host over time. The two genetically different groups of infectious organisms (G1 and G2) are each subdivided into three subgroups based on smaller genetic differences. They are G1-S1, G1-S2, G1-S3, G2-S4, G2-S5, and G2-S6. The hosts must be sacrificed to discover which ones are infected. This results in counts of infected and non-infected hosts. (A critical biological point is that an infected host can become uninfected with time.) For each subgroup an unequal number of hosts are sampled at each of 4 time points such that the results look something like this for one type of host organism. Time point 1Time point 2Time point 3Time point 4 Hosts Inf Not-InfInf Not-InfInf Not-InfInf Not-Inf Tested G1-S11 14 11 4 11 1 13 2 57 G1-S27 8 12 3 14 2 15 8 69 G1-S31 246 18815915 95 G2-S43 12 12 4 10 4 14 2 61 G2-S55 105 68 7 1114 57 G2-S62 26 12 12 1116 1412 105 The questions are how can group 1 (G1) be compare to group 2 (G2) and how can subgroups be compared. I maintain that the heterogeneity within each group does not prevent pooling of the subgroup data within each group, because the groupings were made a priori based on genetic similarity. -- R. Mark Sharp, Ph.D. [EMAIL PROTECTED] Southwest Regional Primate Center Tel: 210-258-9476 Director of Biostatistics and Scientific ComputingFax: 210-258-9883 Southwest Foundation for Biomedical Research P.O. Box 760549 7620 West Loop 410 at Military Drive San Antonio, TX 78245-0549 = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
