Research Fundamentals: Study Design, Population, and Sample Size

Abstract

This is the second article of a three-part series that continues the discussion on the fundamentals of writing research protocols for quantitative, clinical research studies. In this editorial, the author discusses some considerations for including information in a research protocol on the study design and approach of a research study. This series provides a guide for undergraduate researchers interested in publishing their protocol in the Undergraduate Research in Natural and Clinical Sciences and Technology (URNCST) Journal.Keywords: protocol; proposal; study design; population; study setting; sampling; sample size; undergraduate research; clinical research IntroductionThis article continues the discussion on writing a research protocol for a quantitative, clinical research study. In the second part of a three-part series, the author examines the components of a study's design and approach to research inquiry. These components are the type of design, population of interest, study setting, recruitment, and sampling.

What Is the Big Deal About Populations in Research?

“…Instead, we will recruit (or sample) the accessible population, all with the goal of generalizing our findings to our target population. 2 And how closely our sample matches our accessible population impacts how closely our results are generalizable to our target population. Remember, our target population was Caucasian females on the deceased donor transplant list in the United States with the specified GFR during the specified period, while our accessible population was Caucasian females on the deceased donor transplant list at Grey Sloan Memorial Hospital with the specified GFR during the specified period.…”

M-Learning History of Malacca by Using Animated Video for Primary School Standard Curriculum (KSSR)

“…According to [7], a sample represents the sum taken from all selected objects and is considered to represent the whole population. The study samples involved in this study were randomly selected for the purpose of testing the functionality and evaluating the design of the developed application interface.…”

Research Fundamentals: Data Collection, Data Analysis, and Ethics

“…Statistical inferencing is the process of drawing conclusions about an entire population based on a sample from it [8]. For example, to investigate whether or not there is a statistical relationship between postpartum depression and a second pregnancy, researchers may recruit a sample of pregnant women that supposedly represent the entire population.…”

“…Hypothesis testing relies on the null and alternate hypotheses, type I and II errors, significance and power level, and the pvalue, which were discussed in the second editorial of this three-part series on writing research protocols [8]. Hypothesis testing determines whether or not the data is in favour of the null hypothesis (i.e., no significant difference between population and sample means) or alternate hypothesis (i.e., there is a significant difference between population and sample means).…”