Statistics in Medical Research: Misuse of Sampling and Sample Size Determination

Abstract

One of the major issues in planning a research is the decision as to how large a sample and the method to be employed to select the estimated sample in order to meet the objective of the research. Sampling is an essential tool for research in medicine. A good number of the medical literature while reporting their sampling method go by stating that the sample was collected by random sampling and no further explanation as how the sample has been drawn as if the word random is generic to all the known sampling methods. The aim of this paper is to sensitise our researchers on the importance of proper sampling and sample size determination. Using a few examples we demonstrated that investigators adhere poorly to the statistical precondition of simple random sampling, have poor understanding of simple random technique, and quite a number of estimated sample sizes were bloated without appreciating the implications of that. Finally, we recommended, among others that investigators should consult biostatisticians at the design stages of their research work and a competent biostatistician should review any article containing even the most elementary statistical procedure.\u13d'un des questions principales d'un recherch\ue9 pour prendre un d\ue9cision, comment le grande \ue9chantillon et la m\ue9thode d'\ueatre employ\ue9 se s\ue9l\ue9ctionner un \ue9chantillon \ue9stim\ue9 afin d'atteindre le but d'un recherchre. \uc9chantillonnage est un utile essentiale \ue0 la recherche en m\ue9dicine. Le mieux nombre de la litterature de la m\ue9dicine alors que la reportage de leur \ue9chantillonnage m\ue9thode not\ue9 que l'\ue9chantillonnage avait collect\ue9 par l'\ue9chatillonnage al\ue9atoire et pas explication davantage comment l'\ue9chantillon \ue0 \ue9t\ue9 attirer si le mot al\ue9atoire est g\ue9n\ue9rique aux savoir d'al\ue9atoires \ue9chantillonnage. Le but de cette expos\ue9 est pour sensibilser notre rechercheur sur l'importance d'\ue9chantillonnage proper et d\ue9t\ue9rmin la sauter \u10fal\ue9atoire \ue9chatillonnage. Nous avons utiliser quelque examples prouve que les investigateurs mal obeir en la pr\ue9condition statistiques d'al\ue9atoire \ue9chatillonnage simple, ils ont mal comprend la technique \u10fal\ue9atoire simple, et un bon nombre d'\ue9stimer les sauters simple \ue9tait hypertrophi\ue9 sans appr\ue9ciation de l'implication. Finallement, nous avons reccomand\ue9 que entre autres investigateurs devraient consulter les biostatisciens \ue0 l'\ue9tage \u10f\ue9baucher leur travail et un comp\ue9tent biostatisticien devrais en revue l'article contienir m\ueame le plus proc\ue9dure \ue9l\ue9mentaire statistique