Thursday, September 22, 2011

RASCH : Smaller sample size with lesser error..

In determining a practical sample size, one have to understand the method of analysis to be employed. In general practice, sample size by random sampling is done using the table developed by Krejcie &Morgan, (1970) Determining sample size for research activities. J.Educational and Psychological Measurement, 30, 607-610. 

According to Salant and Dillman (1994), the size of the sample is determined by four factors: (1) how much sampling error can be tolerated; (2)population size; (3) how varied the population is with respect to the characteristics of interest; and (4) the smallest subgroup within the sample for which estimates are needed. One of the common reference is Cohen Statistical Power Analysis (1992) being one of the most popular approaches in the behavioural sciences in calculating the required sampling size. In Krejcie and Morgan (1970), the estimated random sampling size for a population of 500 is 217. However, the estimated sampling size calculated using Cohen (1992) differs according to the type of statistical tests employed by the researcher. The sample size that is required for a correlational study is 85 while a multiple regression analysis requires 116.

Rasch statistical analysis offers a better mathematics with even smaller sample size but of sufficient stability. see, "Sample Size and Item Calibration Stability. Linacre JM. Rasch Measurement Transactions 1994 7:4 p.328"Rasch analysis can handsomely handle a sample size of 25-30 to generate a sound 95%CL statistics and 50-60 for a 99% CL.

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