The multivariate asymptotic distribution of sequential Chi-square test statistics is investigated. It is shown that: (a) when sequential Chi-square statistics are calculated for nested models on the same data, the statistics have an asymptotic intercorrelation which may be expressed in closed form, and which is, in many cases, quite high; and (b) sequential Chi-square difference tests are asymp...

Labor intensive experiments are typically required to identify the causal disease variants from a list of disease associated variants in the genome. For designing such experiments, candidate variants are ranked by their strength of genetic association with the disease. However, the two commonly used measures of genetic association, the odds-ratio (OR) and p-value may rank variants in different ...

This research was performed to identify the incidence of deformity of lower extremity and to identify the relationship of the incidence between the deformities. Once the incidences and relationship are found, next purpose was to find the effects of physical characteristics and residence styles on the development of lower extremity deformities. One hundred fifteen males and 108 females participa...

A test for goodness of fit usually involves examining a random sample from some unknown distribution in order to test the null hypothesis that the unknown distribution function is in fact a known, specified function. The Chi-square test can be applied to any univariate distribution for which you can calculate the cumulative distribution function. The Chi-square test does not have good propertie...

Binary outcomes that depend on an ordinal predictor in a non-monotonic way are common in medical data analysis. Such patterns can be addressed in terms of cutpoints: for example, one looks for two cutpoints that define an interval in the range of the ordinal predictor for which the probability of a positive outcome is particularly high (or low). A chi-square test may then be performed to compar...

Let {ηi(t),t∈[0,1]}i=1k be independent copies of η={η(t),t∈[0,1]}, a mean zero continuous Gaussian process. Yk:=Yk(t)= ∑i=1kηi2(t),t∈[0,1]. This paper shows how exact local (at 0) and uniform moduli continuity (on [0,1]) Yk can obtained from the η.