Sample size determination is an important and often difficult step in planning an empirical study. From a statistical perspective, sample size depends on the following factors: type of analysis to be performed, desired precision of estimates, kind and number of comparisons to be made, number of variables to be examined, and heterogeneity of the population to be sampled. Other important considerations include feasibility, such as ethical limitations on access to a population of interest and the availability of time and money. The primary assumption of the book is that, within the context of eth ... More

Sample size determination is an important and often difficult step in planning an empirical study. From a statistical perspective, sample size depends on the following factors: type of analysis to be performed, desired precision of estimates, kind and number of comparisons to be made, number of variables to be examined, and heterogeneity of the population to be sampled. Other important considerations include feasibility, such as ethical limitations on access to a population of interest and the availability of time and money. The primary assumption of the book is that, within the context of ethical and practical limitations, efforts to obtain samples of appropriate size and quality remain an important and viable component of social science research. This text describes the following available approaches for estimating sample size in social work research and discusses their strengths and weaknesses: power analysis; heuristics or rules-of-thumb; confidence intervals; computer-intensive strategies; and ethical and cost considerations. In addition, strategies for mitigating pressures to increase sample size, such as emphasis on model parsimony (e.g., fewer dependent and independent variables), simpler study designs, an emphasis on replication, and careful planning of analyses are discussed. The book covers sample-size determination for advanced and emerging statistical strategies, such as structural equation modeling, multi-level analysis, repeated measures MANOVA, and repeated measures ANOVA which are not discussed in other texts.