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Published on : Mar 09, 2022 | Views : 4044 | Downloads : 19

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RESEARCH METHODOLOGY SEMINAR BY HIMANSHU GAKHAR MPT NEUROLOGY (1ST SEM) AJIPT SAMPLE SIZE CALCULATION
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WHAT IS SAMPLE SIZE?
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The sample size is the number of patients or other experimental units included in a study, and determining the sample size required to answer the research question is one of the first steps in designing a study.
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Why sample size calculations? Optimum sample size determination is required for the following reasons: To allow for appropriate analysis. To provide the desired level of accuracy To allow validity of significance test
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Lack of statistical significance does not mean that there is no treatment effect; however, it is an outcome of small sample size (or low power). Hence adequate sample size and sufficient power is the most important aspect of any research
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How large a sample do i need? If sample is too small… 1. Inaccurate results. 2. More source of bias. 3. Power of the study comes down. 4. Study fails to give meaningful information. 5. Waste of resources on a inaccurate study. 6. Ethical issues about recruiting patients into a meaningless study.
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If the sample size is too large: The study will be difficult Time constraint Available cases e.g. rare disease. Loss of accuracy.
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Factors that affect on the sample size calculation : The type of collective data of the study. The level of precision. The confidence level. The significant level. The effect size. The degree of variability. Type I error (α error). Type II error (β error). Statistical power (1 - β)
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PROCEDURE FOR SAMPLE SIZE CALCULATION There are four procedures that could be used for calculating sample size: Use of formulae Ready made table Computer software
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n = no. of samples N = total population e = error margin / margin of error
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EXAMPLE: Suppose that you have a group of 1,000 city government employees and you want to survey them to find out which of them have more balance deficits. You decide that you are happy with a margin of error of 0.05. Using Slovin's formula, you would be required to survey n = N / (1 + Ne^2) people: 1,000 / (1 + 1000 * 0.05 * 0.05) = 286
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Cochran’s Formula Cochran’s formula is considered especially appropriate in situations with large populations.
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Where: e is the desired level of precision (i.e. the margin of error), p is the (estimated) proportion of the population which has the attribute in question, q is 1 – p. The z-value is found in a Z table.
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Example: Suppose we are doing a study on the inhabitants of a large town, and want to find out how many households do exercise in morning. We don’t have much information on the subject to begin with, so we’re going to assume that half of the families do it: this gives us maximum variability. So p = 0.5. Now let’s say we want 95% confidence, and at least 5 percent—plus or minus—precision. A 95 % confidence level gives us Z values of 1.96, per the normal tables, so we get n = (1.96)2 (0.5) (0.5)) / (0.05)2 = 385. So a random sample of 385 households in our target population should be enough to give us the confidence levels we need.
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Modification for the Cochran Formula for Sample Size Calculation In Smaller Populations Here n0 is Cochran’s sample size recommendation, N is the population size, and n is the new, adjusted sample size. In our earlier example, if there were just 1000 households in the target population, we would calculate 385 / (1 + ( 384 / 1000 )) = 278 So for this smaller population, all we need are 278 households in our sample; a substantially smaller sample size.
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For two independent samples
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Physiotherapy department is conducting a study to measure the difference in caloric intake of lunch between two schools, where one school received hot lunch program while the other did not. Other nutrition studies estimated that the SD in caloric intake among primary school children was 70 calories, and they wished to make their estimate to be within 15 calories intake of the true difference with 95% confidence. What is the required number of children to be studied for the above program?
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It is given that standard deviation in both the groups is 70 and absolute precision is 15.
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For two paired observation
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An investigator wants to associate the change in blood pressure before and after the administration of excercise protocol . If the investigator is observing the difference between the pre (Mean BP = 95) and post test (Mean BP = 85), and between the subjects Standard Deviation as 10, for a 5% error (two sided) and 90% power. How many patients should be needed?
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USE OF READY MADE TABLES
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How large a sample of patients should be followed up if an investigator wishes to estimate the incidence rate of a disease to within 10% of it’s true value with 95% confidence?
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The table show that for e=0.10 & confidence level of 95%, a sample size of 385 would be needed..
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THANK YOU!