经验法则
蒙特卡罗方法
样本量测定
计量经济学
样品(材料)
统计
验证性因素分析
可靠性(半导体)
心理学
结构方程建模
计算机科学
数学
功率(物理)
物理
算法
量子力学
色谱法
化学
作者
Linda K. Muthén,Bengt Muthén
标识
DOI:10.1207/s15328007sem0904_8
摘要
Abstract A common question asked by researchers is, "What sample size do I need for my study?" Over the years, several rules of thumb have been proposed. In reality there is no rule of thumb that applies to all situations. The sample size needed for a study depends on many factors, including the size of the model, distribution of the variables, amount of missing data, reliability of the variables, and strength of the relations among the variables. The purpose of this article is to demonstrate how substantive researchers can use a Monte Carlo study to decide on sample size and determine power. Two models are used as examples, a confirmatory factor analysis (CFA) model and a growth model. The analyses are carried out using the Mplus program (Muthén& Muthén 1998).
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