%0 Journal Article %A Jeffrey A. Walker %T The Opposing Effect of Hedonic and Eudaimonic Happiness on Gene Expression is Correlated Noise %D 2016 %R 10.1101/044917 %J bioRxiv %P 044917 %X Background This paper presents a re-analysis of the gene set data from Fredrickson et al. 2013 and Fredrickson et al. 2015 which purportedly showed opposing effects of hedonic and eudaimonic happiness on the expression levels of a set of genes that have been correlated with social adversity. Fredrickson et al. 2015 used a linear model of fixed effects with correlated error (using GLS) to estimate the partial regression coefficients.Methods The standardized effects of hedonic and eudaimonic happiness on CTRA gene set expression estimated by GLS was compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using a bootstrap t-test, O’Brien’s OLS test, a permutation t test, and the rotation z-test. The GEE estimates were tested using a Wald test with robust standard errors. The performance (type I, type II, and type M error) of all tests was investigated using a Monte Carlo simulation of data modeled after the 2015 dataset.Results Standardized OLS effects (mean partial regression coefficients) of Hedonia and Eudaimonia on gene expression levels are very small in both the 2013 and 2015 data, as well as the combined data.The p-values from all tests fail to reject any of the null models. The GEE estimates and tests are nearly identical to the OLS estimates and tests. By contrast, the GLS estimates are inconsistent between data sets, but in each dataset, at least one coefficient is large and highly statistically significant. The Monte Carlo simulation of error rates shows inflated type I error from the GLS test on data with a similar correlation structure to that in the 2015 dataset, and this error rate increases as the number of outcomes increases relative to the number of subjects. Bootstrap and permutation GLS distributions suggest that the GLS model not only results in downward biased standard errors but also inflated coefficients. Both distributions also show the expected, strong, negative correlation between the coefficients for Hedonia and Eudaimonia.Discussion The results fail to support opposing effects, or any detectable effect, of hedonic and eudaimonic well being on the pattern of gene expression. The apparently replicated pattern of hedonic and eudaimonic effects on gene expression is most parsimoniously explained as "correlated noise" due to the geometry of multiple regression. A linear mixed model for estimating fixed effects in designs with many repeated measures or outcomes should be used cautiously because of the potentially inflated type 1 and type M error. %U https://www.biorxiv.org/content/biorxiv/early/2016/07/07/044917.full.pdf