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Sampling Strategy and Sample Size


The present paper critiques the sampling strategy and sample size of the selected article. Overall, it is evident that the strategies used (e.g., inclusion criteria, stratified sampling, randomization, and power analysis) were effective in maintaining internal validity and ensuring that findings could be generalized to the wider population.

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Sampling is of immense importance in research as it allows scholars to study a proportion of the population and generalize the conclusions across the entire population if the sample is (Creswell, 2009). This paper critiques the sampling strategy and the sample size of a quantitative study titled “A Parent-Adolescent Intervention to Increase Sexual Risk Communication.”

Critique of Sampling Strategy and Sample Size

The study by Villarruel, Cherry, Cabriales, Ronis, and Zhou (2008) recruited 791 participants by inviting adolescents and their parents to participate in a health promotion program. Parents formed the population for the study, with the inclusion criteria for selection being participation in the program and having an adolescent in the family. In retrospect, purposive sampling should have been used here as it enables a focus on specific characteristics of the population that are of interest to the researchers (Frankfort-Nachmias, Nachmias, & DeWaard, 2014).

Stratified sampling was used to group participants according to the number of adolescents in their family and gender, before random sampling was applied to assign participants to the experimental and control groups (Villarruel et al., 2008). These are the major tenets of stratified sampling that enable researchers to group the sample according to key characteristics and also to randomize participants from different strata (Frankfort-Nachmias et al., 2014). The power analysis done demonstrated the sample size was sufficient as it had 91% statistical power to identify a medium small effect (d =.25) of the intervention on outcome (Villarruel et al., 2008). Other analyses (e.g., mediation analysis) proved that the sample could be relied upon to establish the required effect, though researchers failed to offer a description of these techniques.

Justification of Sample Size

The analyses described above justified the sample size as sufficient. Failure to justify the sample could lead to adverse outcomes such as inability to get the data required to make a correct decision on a particular research and lack of credible study findings (Creswell, 2009).

Strengths and Limitations of Study due to Sampling Strategy

The sampling strategy used ensured that the study results not only demonstrated the effect of the intervention based on the characteristics of each subpopulation, but could also be relied upon due to the power and effectiveness of the sample. Additionally, the analyses done on sample size ensured the correctness of the sample, minimized sampling error and enhanced heterogeneity characterization, which in turn reinforced the generalizability of findings (Wagner & Esbensen, 2015). Lastly, the stratified sampling technique used in the study saved money and time resources as it uses a smaller sample compared to random sampling due to its greater precision (Uprichard, 2013). However, limitations existed in terms of difficulties in classifying members of each subpopulation according to specific characteristics as well as sorting each member of the selected sample into a single stratum (Creswell, 2009).

Analysis of Sampling Strategy

An effective sampling strategy can strengthen a quantitative study by ensuring that the findings can be generalized to a wider population and also by dealing with threats to internal and external validity. According to Witter (2002), randomization is easy to use and controls for confounding factors that may compromise the internal validity of the study. However, a poor sampling strategy can weaken a quantitative study in terms of undercoverage (leaving out some groups of the population during sampling), non-responsiveness (individuals refusing to participate in a study after selection), as well as producing divergent and often erroneous inferences (Bhattacherjee, 2012).

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This paper critiqued the sampling strategy and sample size of the selected article. Overall, it is evident that the sampling strategy used is effective in ensuring that the findings maintained their internal validity and could be generalized to a wider population.


Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. New York City: Springer.

Creswell, J.W. (2009). Research design: Qualitative, Quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage Publications Inc.

Frankfort-Nachmias, C., Nachmias, D., & DeWaard, J. (2014). Research methods in the social sciences (8th ed.). New York: Worth Publishers.

Uprichard, E. (2013). Sampling: Bridging probability and non-probability designs. International Journal of Social Research Methodology, 16(1), 1-11.

Villarruel, A.M., Cherry, C.L., Cabriales, E.G., Ronis, D.L., & Zhou, Y. (2008). A parent-adolescent intervention to increase sexual risk communication: Results of a randomized controlled trial. AIDS Education and Prevention, 20(5), 371-383.

Wagner, C., & Esbensen, K.H. (2015). Theory of sampling: Four critical success factors before analysis. Journal of AOAC International, 98(2), 275-281.

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Witter, J. (2002). Sample size calculations for randomized controlled trials. Epidemiologic Reviews, 24(1), 39-53.

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