The chi-square test of independence.

The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data.

Interrater reliability: the kappa statistic.

The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability.

Multiple comparison analysis testing in ANOVA.

The Analysis of Variance (ANOVA) test has long been an important tool for researchers conducting studies on multiple experimental groups and one or more control groups. However, ANOVA cannot provide detailed information on differences among the various study groups, or on complex combinations of study groups. To fully understand group differences in an ANOVA, researchers must conduct tests of the differences between particular pairs of experimental and control groups.

The role of caregiver gender and caregiver burden in nursing home placements for elderly Taiwanese survivors of stroke.

The role of caregiver gender in caregiver burden and the association between the level of caregiver burden and institutionalization of elderly stroke survivors in Taiwan were explored using a correlational, descriptive design. The convenience sample was composed of 78 male and 69 female primary caregivers of stroke survivors. Simple multiple regression and t tests were used to test the research questions.

Descriptive statistics, Part II: Most commonly used descriptive statistics.

Descriptive measures can reveal a great deal of information about any variable of interest, whether the data be clinical, administrative, educational, or research data. To make best use of a descriptive statistic, it is important to know what levels of measurement should be used with the statistic, and what information the statistic can provide. To find out about the most typical case, measures of central tendency are appropriate.