Quantitative Research Population and Estimated Population Size
The proposed quantitative study aims to evaluate the efficacy of public health interventions, introduced in 2012, to manage cholera. The sample population would include public health practitioners that have a vast knowledge of public health interventions in Sierra Leone and their effects on local populations. The proposed study would sample 50 respondents who hail from different districts where health agencies introduced interventions to manage cholera in 2012. The respondents should have a vast knowledge about the efficacy of existing interventions and possess adequate knowledge regarding the incidence of cholera in their jurisdictions. The respondents would be government officials and professionals who work in the upper echelons of health management in their respective organizations.
Sampling Strategy and Sample Size
The proposed study would use a probability sampling strategy where the researcher knows the probability of choosing each respondent. Such sampling methods normally occur when researchers use some form of random selection in choosing the respondents (Neill, 2003). Furthermore, this sampling strategy will allow the researcher to select units from a specific population sample. The main purpose of using this sampling method is to come up with a “generalizable” sample and to minimize the sampling bias. The sampling method will also allow the researcher to make statistical inferences. Using the probability sampling method, the paper will source respondents using the cluster sampling method. The cluster sampling method is appropriate for the study because, in 2012, health agencies introduced the above-mentioned interventions in distinct districts of Sierra Leone (World Health Organization, 2012). These districts will form N groups (clusters) for sampling.
The rationale for Sampling Strategy
The main motivation for using the cluster sampling method is the low cost of implementing it. For example, the cost of obtaining information about every cluster is less than the cost of using alternative sampling strategies (Dessel, 2013). Furthermore, it is difficult to compile a list of population elements affected by the cholera interventions because the process would be costly and time-consuming. A practical sampling strategy would be randomly selecting a subset of public health officials who are knowledgeable about the effects of the cholera interventions in their respective jurisdictions and getting this information from them. This strategy is not only practical but also cheaper. The low cost justifies the loss in precision that is often associated with using cluster-sampling methods. Dessel (2013) supports the use of the cluster sampling strategy in research papers, especially if the population is concentrated in natural clusters, as it is in Sierra Leone.
Strengths and Weaknesses of the Sampling Strategy
This paper has already shown that the proposed study would use a cluster sampling method, which is a probabilistic sampling method. Therefore, there would be no need to have detailed information about the respondents, or their respective clusters gather reliable findings. Furthermore, researchers have established that most probability-sampling techniques, such as the cluster sampling method, are unbiased and have a relatively reliable measurable precision (Neill, 2003). They have also affirmed that this sampling design allows researchers to gauge the relative efficiency of their sampling plan (Neill, 2003). This ability would help to ascertain the validity and reliability of the research findings. The main disadvantage of this sampling strategy may be the reduced effectiveness that would occur if the members of different units have different characteristics.
Considerations when Choosing Sample Size
Getting the correct sample size is often a difficult task for many researchers because they do not (often) know which sample size would be enough to come up with reliable findings. However, according to Creative Research Systems (2012), this task should not be difficult because researchers should consider the sample population, the margin of error, confidence level, and standard of deviation as the main determinants of sample size. These issues also played a vital role in informing my decision to choose the correct sample size for the proposed study. For example, the total number of respondents sampled within one province should correspond to the size of the population sampled. Therefore, if one province has 1,000,000 people, the total number of respondents should be higher than a province that has only 500,000 people. The margin of error is another consideration that informed my choice of the sample size. Since there is no perfect sample, it is important to consider the allowable margin of error in the study. If there is little room for error, the sample size should be big. Similarly, a higher margin of error would allow for a smaller sample size (Creative Research Systems, 2012). These considerations informed my sample size.
References
Creative Research Systems. (2012). Sample Size Calculator: The Survey System. Web.
Dessel, G. (2013). How to determine population and survey sample size? Web.
Neill, J. (2003). Quantitative Research Design: Sampling & Measurement. Web.
World Health Organization. (2012). Cholera in Sierra Leone: the case study of an outbreak. Web.