scholarly journals Sample Size Determination in Survey Research

2020 ◽  
pp. 90-97 ◽  
Author(s):  
Anokye M. Adam
Keyword(s):  
Sample Size ◽  
Survey Research ◽  
Sample Size Determination ◽  
Categorical Variables ◽  
Size Determination ◽  
Population Variance ◽  
Optimum Sample Size ◽  
Margin Of Error ◽  
Optimum Sample ◽  
Sample Estimate

Obtaining a representative sample size remains critical to survey researchers because of its implication for cost, time and precision of the sample estimate. However, the difficulty of obtaining a good estimate of population variance coupled with insufficient skills in sampling theory impede the researchers’ ability to obtain an optimum sample in survey research. This paper proposes an adjustment to the margin of error in Yamane’s (1967) formula to make it applicable for use in determining optimum sample size for both continuous and categorical variables at all levels of confidence. A minimum sample size determination table is developed for use by researchers based on the adjusted formula developed in this paper.

scholarly journals Optimum sample size to estimate mean parasite abundance in fish parasite surveys

2018 ◽  
Vol 55 (1) ◽  
pp. 52-59 ◽  
Author(s):  
S. Shvydka ◽  
V. Sarabeev ◽  
V. D. Estruch ◽  
C. Cadarso-Suárez
Keyword(s):  
Sample Size ◽  
Sample Size Determination ◽  
Superior Performance ◽  
Size Determination ◽  
Optimum Sample Size ◽  
True Value ◽  
Wide Range ◽  
Precision Level ◽  
The Mean ◽  
Optimum Sample

Summary To reach ethically and scientifically valid mean abundance values in parasitological and epidemiological studies this paper considers analytic and simulation approaches for sample size determination. The sample size estimation was carried out by applying mathematical formula with predetermined precision level and parameter of the negative binomial distribution estimated from the empirical data. A simulation approach to optimum sample size determination aimed at the estimation of true value of the mean abundance and its confidence interval (CI) was based on the Bag of Little Bootstraps (BLB). The abundance of two species of monogenean parasites Ligophorus cephali and L. mediterraneus from Mugil cephalus across the Azov-Black Seas localities were subjected to the analysis. The dispersion pattern of both helminth species could be characterized as a highly aggregated distribution with the variance being substantially larger than the mean abundance. The holistic approach applied here offers a wide range of appropriate methods in searching for the optimum sample size and the understanding about the expected precision level of the mean. Given the superior performance of the BLB relative to formulae with its few assumptions, the bootstrap procedure is the preferred method. Two important assessments were performed in the present study: i) based on CIs width a reasonable precision level for the mean abundance in parasitological surveys of Ligophorus spp. could be chosen between 0.8 and 0.5 with 1.6 and 1x mean of the CIs width, and ii) the sample size equal 80 or more host individuals allows accurate and precise estimation of mean abundance. Meanwhile for the host sample size in range between 25 and 40 individuals, the median estimates showed minimal bias but the sampling distribution skewed to the low values; a sample size of 10 host individuals yielded to unreliable estimates.

scholarly journals Relevance of Sample Size Determination in Medical Research

1970 ◽  
Vol 1 (1) ◽  
pp. 4-10 ◽  
Author(s):  
Brijesh Sathian ◽  
Jayadevan Sreedharan ◽  
Suresh N Baboo ◽  
Krishna Sharan ◽  
E S Abhilash ◽  
...  
Keyword(s):  
Medical Research ◽  
Sample Size ◽  
Power Analysis ◽  
Sample Size Determination ◽  
Large Sample Size ◽  
Size Determination ◽  
Optimum Sample Size ◽  
Significant Difference ◽  
Optimum Sample ◽  
Made In

Sample size determination is one of the central tenets of medical research. If the sample size is inadequate, then the study will fail to detect a real difference between the effects of two clinical approaches. On the contrary, if the sample size is larger than what is needed, the study will become cumbersome and ethically prohibitive. Apart from this, the study will become expensive, time consuming and will have no added advantages. A study which needs a large sample size to prove any significant difference in two treatments must ensure the appropriate sample size. It is better to terminate such a study when the required sample size cannot be attained so that the funds and manpower can be conserved. When dealing with multiple sub-groups in a population the sample size should be increased the adequate level for each sub-group.  To ensure the reliability of final comparison of the result, the significant level and power must be fixed before the sample size determination. Sample size determination is very important and always a difficult process to handle. It requires the collaboration of a specialist who has good scientific knowledge in the art and practice of medical statistics. A few suggestions are made in this paper regarding the methods to determine an optimum sample size in descriptive and analytical studies.Key Words: Sample size; Power analysis; Medical researchDOI: 10.3126/nje.v1i1.4100Nepal Journal of Epidemiology 2010;1 (1):4-10

scholarly journals Sample Size for Survey Research: Review and Recommendations

2020 ◽  
Vol 4 (2) ◽  
pp. i-xx ◽  
Author(s):  
Mumtaz Ali Memon ◽  
Hiram Ting ◽  
Jun-Hwa Cheah ◽  
Ramayah Thurasamy ◽  
Francis Chuah ◽  
...  
Keyword(s):  
Sample Size ◽  
Survey Research ◽  
Power Analysis ◽  
Sample Size Determination ◽  
Research Review ◽  
Size Determination ◽  
Fundamental Understanding ◽  
Rules Of Thumb ◽  
Research Findings ◽  
Calculate Sample Size

Determining an appropriate sample size is vital in drawing realistic conclusions from research findings. Although there are several widely adopted rules of thumb to calculate sample size, researchers remain unclear about which one to consider when determining sample size in their respective studies. ‘How large should the sample be?’ is one the most frequently asked questions in survey research. The objective of this editorial is three-fold. First, we discuss the factors that influence sample size decisions. Second, we review existing rules of thumb related to the calculation of sample size. Third, we present the guidelines to perform power analysis using the G*Power programme. There is, however, a caveat: we urge researchers not to blindly follow these rules. Such rules or guidelines should be understood in their specific contexts and under the conditions in which they were prescribed. We hope that this editorial does not only provide researchers a fundamental understanding of sample size and its associated issues, but also facilitates their consideration of sample size determination in their own studies.

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