Methodological iseues in the analysis of incidence rates or prevalence proportions for count data, presented in a form of a sequence of 2 X 2 tables, corresponding to levels (strata) of a specified variable (risk factor) X, are discussed. Suppose Ali and A2i are the incidence rates of an event D in the ith stratum for populations 1 and 2, respectively. The homogeneity (null) hypothesis is formulated in the form: Ho:Aig=Azi for all i (i=1, 2, ..., I). Three Xz-teeta for HO and their theoreticcrl bases are d i e c u d : X$,bl which is sensitive to alternatives Hq):Alc +A% for a t least some i; X&, mb whichis sensitive toalternatives H q ) : h > A z ( o r A2i for some i and A1i\-=Azit for some i' ( i \ i ' ) . Them statistics satisfy the relation X~,,l=X&,rnb +X&,. Also, X'2-statistic for pooled data is calculated, which in conjunction with XEornb can serve for detecting confounding. Although most of these techniques are known, they are rather scattered in the literature, and not always considered jointly, as i t is emphasized in the present paper. It is hoped that these comments will be helpful to biostatisticians as well as to epidemiologists and medical researchers in the analysis of mortality and morbidity data. For illustration, two examples with large sete of epidemiological data are given.