Atkins David C, Gallop Robert J
Travis Research Institute, Fuller Graduate School of Psychology, Pasadena, CA 91101, USA.
J Fam Psychol. 2007 Dec;21(4):726-35. doi: 10.1037/0893-3200.21.4.726.
Marital and family researchers often study infrequent behaviors. These powerful psychological variables, such as abuse, criticism, and drug use, have important ramifications for families and society as well as for the statistical models used to study them. Most researchers continue to rely on ordinary least-squares (OLS) regression for these types of data, but estimates and inferences from OLS regression can be seriously biased for count data such as these. This article presents a tutorial on statistical methods for positively skewed event data, including Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. These statistical methods are introduced through a marital commitment example, and the data and computer code to run the example analyses in R, SAS, SPSS, and Mplus are included in the online supplemental material. Extensions and practical advice are given to assist researchers in using these tools with their data.
婚姻与家庭研究者常常研究不常发生的行为。这些强大的心理变量，如虐待、批评和吸毒，对家庭和社会以及用于研究它们的统计模型都有重要影响。大多数研究者在处理这类数据时仍继续依赖普通最小二乘法（OLS）回归，但对于此类计数数据，OLS回归的估计和推断可能会出现严重偏差。本文提供了关于正偏态事件数据统计方法的教程，包括泊松回归、负二项回归、零膨胀泊松回归和零膨胀负二项回归模型。通过一个婚姻承诺的例子介绍了这些统计方法，在线补充材料中包含了在R、SAS、SPSS和Mplus中运行示例分析的数据和计算机代码。文中还给出了扩展内容和实用建议，以帮助研究者将这些工具应用于他们的数据。
