Interference of sample size on multicollinearity diagnosis in path analysis

被引：9

作者：

Sari, Bruno Giacomini ^{[1
]}

Lucio, Alessandro Dal'Col ^{[1
]}

Olivoto, Tiago ^{[1
]}

Krysczun, Dionatan Ketzer ^{[1
]}

Tischler, Andre Luis ^{[1
]}

Drebes, Lucas ^{[1
]}

机构：

[1] Univ Fed Santa Maria, Dept Fitotecnia, Ave Roraima 1-000, BR-97105900 Santa Maria, RS, Brazil

来源：

PESQUISA AGROPECUARIA BRASILEIRA | 2018年 / 53卷 / 06期

关键词：

Solanum lycopersicum; bootstrapping; multivariate analysis; sampling;

D O I：

10.1590/S0100-204X2018000600014

中图分类号：

S [农业科学];

学科分类号：

09 ;

摘要：

The objective of this work was to evaluate the interference of sample size on multicollinearity diagnosis in path analysis. From the analyses of productive traits of cherry tomato, two Pearson correlation matrices were obtained, one with severe multicollinearity and the other with weak multicollinearity. Sixty-six sample sizes were designed, and from the amplitude of the bootstrap confidence interval, it was observed that sample size interfered on multicollinearity diagnosis. When sample size was small, the imprecision of the diagnostic criteria estimates interfered with multicollinearity diagnosis in the matrix with weak multicollinearity.

引用

页码：769 / 773

页数：5

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