With reference to contemporary research studies, critically highlight the advantages and disadvantages of qualitative methodology to public health research.
This test is used in situations where there are more than two levels of the grouping component, observations are matched or they are measured more than once, the data are at least interval. In experimental designs, it\’s a just right notion to measure the subjects several times. These multiple measurements are named trails. The Cochran Q test (also a nonparametric test) is preferably used when the k related samples are measured on a nominal scale. It checks the hypothesis that the proportion of cases in one category is equal for various associated categories. The Friedman two-way analysis of variance can also be preferable to use when the data are ordinal. It examines the matched samples, ranking every one of the cases and calculating the mean rank for each variable for all cases. Other nonparametric significance tests One-Sample Case Kolmogorov-Smirnov Test The Kolmogorov – Smirnov test is suitable to use when the data are ordinal and the research needs to compare the observed sample distribution with the theoretical distribution. In this case, the Kolmogorov-Smirnov test (KS) is more applicable than the chi-square test. It can be used for small samples when other tests like Chi-square test, for instance, cannot be used. The theoretical distribution shows the researcher’s expectations under the null hypothesis H0. We determine the D (maximum deviation) which is the point of the great divergence, or in other words, the greatest variation, between the observed and theoretical distribution. It is calculated as follows: D=maximum |F0 (X) – FT (X) | In which:>GET ANSWER