CORRELATIONAL METAANALYSIS - INDEPENDENT AND NONINDEPENDENT CASES
CORRELATIONAL METAANALYSIS - INDEPENDENT AND NONINDEPENDENT CASES
复制标题
DOI：
10.1177/0013164492052004007
复制
发表时间：
1992-12-01
影响因子：
2.7
通讯作者：
POHLMANN, JT
中科院分区：
文献类型：
--
作者：
TRACZ, SM;ELMORE, PB;POHLMANN, JT
本研究的目的是确定在荟萃分析中结合相关系数时违反独立性假设的影响。在该蒙特卡罗模拟中，使用了以下四个参数和指定的值：N-研究中的样本量（20，50，100），p-预测因子的数量（1，2，3，5），rho（i）-预测因子之间的群体相关性（0，.3，.7），rho（p）-预测因子和标准之间的群体相关性（0，.3，.7）。当只使用一个预测因子或当预测因子之间的相关性等于零时，不违反独立性假设。当使用一个以上的预测因子的相关性超过零时，违反了独立性的假设。因此，rho（i）非独立性指数是主要的关注参数。对于r's和Fisher's z's，平均值、中位数和标准差在rho（i）或p水平上没有明显变化，但随着N的增加，预期值的估计精度提高。r's和Fisher's z's的90%、95%和99%置信区间显示rho（i）或p水平无变化，但区间随N增加而缩小。
The purpose of this study was to determine the effect of the violation of the assumption of independence when combining correlation coefficients in a meta-analysis. In this Monte Carlo simulation the following four parameters were used with the values specified: N-the sample size within a study (20, 50, 100), p-the number of predictors (1, 2, 3, 5), rho(i)-the population intercorrelation among predictors (0, .3, .7), rho(p)-the population correlation between predictors and criterion (0, .3,.7). When only one predictor was used or when the intercorrelation among predictors equaled zero, the assumption of independence was not violated. The assumption of independence was violated when more than one predictor with an intercorrelation exceeding zero were used. Therefore, rho(i) the index of nonindependence was the main parameter of interest. For both r's and Fisher's z's, the means, medians, and standard deviations showed no discernible change over levels of rho(i) or p, but the precision of estimation of the expected values improved as N increased. The 90%, 95%, and 99% confidence intervals for both r's and Fisher's z's showed no change over levels of rho(i) or p, but the intervals narrowed as N increased.