AUTOEVALUACIÓN DEL RECTOR: COMPETENCIAS GERENCIALES

The process by which samples are obtained from a population is called sampling.

There are two main types of sampling: probability and non-probability sampling. The difference between the two types is whether or not the sampling selection involves randomization. Randomization occurs when all members of the sampling frame have an equal opportunity of being selected for the study. Following is a discussion of probability and non-probability sampling and the different types of each.

i. Probability Sampling – Uses randomization and takes steps to ensure all members of a population have a chance of being selected. The different types of probability sampling include simple random sampling, stratified sampling, cluster sampling, multistage sampling, and systematic random sampling

ii. Non-probability Sampling – Does not rely on the use of randomization techniques to select members. This is typically done in studies where randomization is not possible in order to obtain a representative sample. Bias is more of a concern with this type of sampling. The different types of non-probability sampling include convenience or accidental sampling, purposive sampling, expert sampling, quota sampling and snowball sampling.

3.4.1 Probability Sampling Methods Simple Random Sampling

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A sample selected in such a way that every element in the population has an equal probability of being chosen is known as a random sample. Random samples are obtained by either sampling with replacement from a finite population or by sampling without replacement from an infinite population. To select a simple random sample, first assign a number to each element in the sampling frame. This is usually done sequentially using the same number of digits for each element. Then pick as many numbers from the table of random numbers with that number of digits as are needed for the sample size desired.

Systematic Sampling

One of the easiest-to-use methods for approximating a random sample is the systematic sampling method. This is a sample in which every k^th item in the sampling frame is selected after a random start among the first K elements.

For example, if we desire a 10% systematic sampling, we would determine the position of the first element by using the random number table to randomly select a number between 1 and 10. Suppose the random number table gives 6, then the first element to be picked would come from the 6^th position on the sampling frame. Then the second will be from the 16^th position, the third from the 26^th position and so on.

Stratified Sampling

When sampling very large populations, sometimes it is possible to divide the population into sub-populations on the basis of some characteristics. These sub-populations are called strata. A stratified sampling is obtained by stratifying the sampling frame and then selecting a fixed number of items from each of the strata by means of random sampling.

When a stratified sample is to be drawn, the population is subdivided into the various strata and then a sub-sample is drawn from each stratum. These sub-samples may be drawn from each stratum randomly or systematically. Then the sub-samples are summarized separately and this information is combined to draw conclusions about the whole population. Examples of this include:

i. Students in a faculty stratified by their department ii. Income groups – upper, middle and low-income groups.

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Cluster Sampling

A cluster sampling is obtained by stratifying the sampling frame and then selecting all of the items from some, but not all, of the clusters. The cluster sample is obtained by using either random numbers or a systematic method to identify the strata (clusters) to be sampled and then using all the items from within these clusters. Then the sub-samples are summarized separately and this information is combined.

For example, to study the living condition in the six geopolitical regions in Nigeria, three geopolitical regions are randomly selected. Then all units in the cluster sample are studied. This study of all the units makes cluster sampling sometimes unattractive.

Two-Stage Sampling

A two-stage sampling is obtained at two stages. The first stage involves the division of the population into what is known as primary sampling units (PSU‟s). This first sampling involves a group of individuals in the population put on the basis of their closeness or proximity. A frame of secondary units (SU‟s) is selected from the PSU‟s corresponding to individuals in the population, through random sampling or systematic sampling. For example, in a study of Universities in Lagos State, the primary sampling units can be the University and the secondary units the departments in the University.

This can be extended to three of more stage sampling. For example, the third stage would involve the students in the university.

3.4.2 Non Probability Sampling Methods or Non Random Sampling Methods Quota Sampling

Samples that are selected on the basis of being “typical” and with no definite probability law associated with the selection procedure are known as quota sampling. When a quota sample is drawn, the person selecting the sample chooses items that he or she thinks are representative of the population. The validity of the results from a quota sampling reflects the soundness of the collector‟s judgment. For example, when a study of people‟s idea of a government policy is carried out with the restriction to conduct interview on 100 people each from three major languages; Yoruba, Ibo and Hausa.

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Others are:

i. Judgment or Purposive sampling ii. Convenience sampling

4.0 CONCLUSION

This module has covered various study designs known to clinical trial and epidemiology.

Fundamental terms and concepts are also covered.

5.0 SUMMARY

In this unit, medical terms associated with statistics were defined and expatiated. The basic terms include: Clinical, Epidemiological, Cross-sectional studies, Cohort studies, Case-control studies, Longitudinal studies etc. Sampling and common sampling methods were discussed.

6.0 TUTOR-MARKED ASSIGNMENT 1. Definition the following terms:

i. Incidence ii. Prevalence iii. Screen Test iv. Clinical Trial

v. Epidemiological Studies

2. Differentiate between:

i. Clinical Trial and Epidemiological Studies ii. Experimental studies and Observational studies iii. Panel study and Retrospective study

iv. Case-control studies and Cross-sectional studies.

v. Probability sampling and Non-Probability sampling

References and Further Readings:

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Department of Mathematics (2015). A First Course in Statistics. Department of Mathematics, University of Lagos, Akoka-Yaba, Lagos, Nigeria.

Degu G. and Tessema F. (2007). Biostatistics. In collaboration with the Ethiopia Public Health Training Initiative, The Carter Center, the Ethiopia Ministry of Health, and the Ethiopia Ministry of Education.

Indrayan A. (2017). Statistical Medicine: An emerging medical specialty. J Postgrad Med. Available from: http://www.jpgmonline.com/text.asp?2017/63/4/252/216438.

Volume 63, (4) 252 – 256.

National Library of Medicine. Epidemiology Studies. National Institutes of Health, 9000 Rockville Pike, Bethesda, Maryland 20892U.S. Department of Health and Human Services. https://toxtutor.nlm.nih.gov/05-003.html.

Petrie A. and Sabin C.(2005). Medical Statistics at a Glance. Published by Blackwell Publishing Ltd, USA.

Song, J. W., & Chung, K. C. (2010). Observational studies: cohort and case-control studies. Plastic and reconstructive surgery, 126(6), 2234–2242.

https://doi.org/10.1097/PRS.0b013e3181f44abc

Study Design 101 by Himmelfarb Health Sciences Library. 2011-2019, The Himmelfarb

Health Sciences Library.

Suresh, K., Thomas, S. V., & Suresh, G. (2011). Design, data analysis and sampling techniques for clinical research. Annals of Indian Academy of Neurology, 14(4), 287–290.

https://doi.org/10.4103/0972-2327.91951

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UNIT 3: DATA PRESENTATION: TABULAR AND GRAPHICAL