Ferraro K F, Wilmoth J M
Department of Sociology, Purdue University, West Lafayette, Indiana 47907-1365, USA.
J Gerontol B Psychol Sci Soc Sci. 2000 May;55(3):S173-89. doi: 10.1093/geronb/55.3.s173.
This study compares the use of the binary disease variables with counts of the same conditions in models of self-rated health to better understand the advantages and disadvantages of each approach. In particular, the analysis seeks to determine if statistical power is adequate for the binary variable approach.
Morbidity measures from adults in 2 large national surveys were used in both cross-sectional and longitudinal analyses.
Although differences across the approaches are modest, the binary variable approach offers greater explanatory power and slightly higher R2 values. Despite these advantages, statistical power is insufficient in some cases, especially for conditions that are relatively rare and/or that manifest modest differences on the outcome variable.
Statistical power estimates are advisable when using the binary variable approach, especially if the list of diseases and health conditions is extensive. Although a simple count of diseases may be useful in some research applications, separate counts for serious and nonserious conditions should be more useful in many research projects while avoiding the risk of inadequate statistical power.
本研究比较在自评健康模型中使用二元疾病变量与相同疾病计数的情况，以更好地理解每种方法的优缺点。特别是，该分析旨在确定二元变量方法的统计效力是否足够。
在两项大型全国性调查中，使用了成年人的发病率测量数据进行横断面分析和纵向分析。
尽管不同方法之间的差异不大，但二元变量方法具有更大的解释力和略高的R2值。尽管有这些优点，但在某些情况下统计效力不足，特别是对于相对罕见和/或在结果变量上表现出适度差异的疾病。
使用二元变量方法时，建议进行统计效力估计，特别是如果疾病和健康状况列表很长。虽然简单的疾病计数在某些研究应用中可能有用，但在许多研究项目中，对严重和非严重状况进行单独计数可能更有用，同时避免统计效力不足的风险。
