Sampling Strategy and Sample Size for a Quantitative Research Plan

Running head: Sampling strategy and sampling size

Sampling strategy and sampling size 5

Sampling strategy and sampling size

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Introduction

It is very difficult for researchers to make direct observations to everyone in the population in which they are studying. Due to this fact, they collect data about the population from a sample, which is a subset of individuals. A sample is a group of people who participate in a study or an investigation. Sampling is the process of choosing those who a researcher needs to engage from a population. The population is the group of individuals from where a sample is to be obtained. Generalizability is how we can implement the inferences and interpretations of research to the population of study. They then use these observations to construct inferences concerning the overall population. The agenda of the sample and the sampling strategy is to enhance generalizability of the study. The most crucial feature of any research is its capability to be generalized to the overall population. This gives the research a more scientific value. However, if the interpretations and inferences gathered from a sample are not inferred, we say that the research has a trivial scientific value. If a sample gives a detailed information about the targeted population, then the inferences obtained from the sample can be implemented.

Population

This study involves adults of ages between 15 and 45 years of both genders diagnosed with Schizophrenics and are taking Complementary Medicine for Schizophrenics. The participants I studied have been taking the dosage for eight months or less. Most of them participated in a face-to-face or a web-based disease-specific support for six months and ten months. Most of them are not in the remission and relapse stage that is life gets back to normal. There is no overall consensus of the population diagnosed with Schizophrenics. However, according to NIMH, the number of people who suffer from Schizophrenics in the USA is about 2.2 million individuals (Nachmias & Frankfort-Nachmias, 2008).

Type of sampling

In this study, I employed the quasi-experimental design. This design enabled me to utilize both the face-to-face support and the web-based disease-specific support between six and ten months. The agenda of this strategy is to gather a probability sample that ensures that each in the involved population has an equal opportunity to be part of the sample. This sample is collected in a random manner. This lowers the instances of the non-representative sample. The next aim is to remove those not diagnosed with Schizophrenics or are taking a dosage for at least eight months and also those in remission and relapse stage. I will then employ the systematic sampling. This method chooses the subjects in a logical or orderly manner. I will list all the participants in a specified interval. I will then divide the number of individuals by the number of people I need to the sample and get a value n. If now you consider each nth name, you will obtain a systematic sample of the appropriate or correct size. For instance if I get 300 responses and I need 37 participants, I would take 300 as the number of people in the population then I divide by 37 which is the number of people I need to the sample. This is 300/37 which equals to 8.12 or 13. We say it is a 1-in-8 systematic sample (Marques, 2011).

How the sample will be drawn

To gather participation in face-to-face support, I will pay a visit to various medical centers that deal with Schizophrenics. I will also make an advertisement in various mental disorder support groups. For those who participate in the web-based disease-specific support, I will request them through calling for participation in some forums. The responses to these adverts will be chosen through systematic sampling. (Somekh & Lewin, 2005)

Sample size

Take into consideration that we do not know the exact individuals suffering from Schizophrenics. This study involves a few participants. For this case, I used the Cohen’s d test for two samples. The sample size should accommodate 37 participants in each interval. From the inversion formula from (Nachmias & Frankfort-Nachmias, 2008) which is SE-s/sqrt n, n=s2/SE2, I gathered 37 participants per group. From our two methods, making use of 37 participants per group is an appropriate size. The reason as to why I selected this sample size is because I wanted to maximize the cases of uncovering a particular mean difference. Using larger samples increases the possibilities of obtaining a significant difference. This is so because they reliably show or reflect the population mean or the systematic sample. However, they will cost you more.

References Marques, S. &. (2011). Living in gray areas: Industrial and psychological health. New York: Journal of Environmental Psychology, 31(4), 314-322. doi:10.1016/j.jenvp.2010.12.002. Nachmias, D., & Frankfort-Nachmias, C. (2008). Research methods in the social sciences. New York: St. Martin's Press. Somekh, B., & Lewin, C. (2005). Research methods in the social sciences. London: SAGE Publications.