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Selective Data Analysis in Brown et al.'s Continued Critical Reanalysis

  • Barbara L. Fredrickson

    blf@unc.edu

    Affiliation Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America

Selective Data Analysis in Brown et al.'s Continued Critical Reanalysis

  • Barbara L. Fredrickson
PLOS
x

In their latest critique [1], Brown et al. verify the primary statistical results of our 2015 PLoS ONE report [2]. The results Brown et al. report for their mixed effect linear model analyses of our Confirmation study and pooled Discovery and Confirmation studies in their Table 3 [1] are nearly identical to the results we reported in our Tables 2 and 3 [2].

Nevertheless, Brown et al. continue to dispute the conclusions that follow from these results. They do so by selectively re-analyzing our Discovery study dataset (N = 76), which represents only 25% of the data presented in our 2015 report. Using this approach, Brown et al. argue that the relationship between eudaimonic well-being and gene expression is sensitive to (1) the inclusion vs. exclusion of a single data case (SOBC1-1293), and (2) the effects of a coding error in the originally posted covariate data for another data case (SOBC1-1299). However, analysis of the full set of data presented in our Discovery and Confirmation studies (N = 198) reveals that the association of eudaimonic well-being with gene expression is not materially affected by either of these factors (see Table 1 herein).

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Table 1. Association of well-being with gene expression: pooled Discovery and Confirmation Studies (omitting Discovery study participant SOBC1_1293 or using uncorrected race covariate value for Discovery study participant SOBC1_1299).

https://doi.org/10.1371/journal.pone.0160565.t001

The mixed effect linear model analyses reported in Table 1 account for correlation among the multiple indicator genes examined [3] and continue to indicate a significant inverse relationship between eudaimonic well-being and gene expression, regardless of SOBC1-1293 exclusion or the SOBC1-1299 coding error. (Because SOBC1-1293 and SOBC1-1299 come from the Discovery study sample, they have no effect on analyses of the Confirmation study dataset alone [N = 122] or the Generalization study dataset [N = 107].) The Discovery study sample alone is too small to provide a well-powered mixed effect linear model analysis. Thus, it is unsurprising that Brown et al.’s Table 4 [1] shows non-significant regression coefficients for eudaimonic well-being and point estimates that vary substantially from those of the better-powered analyses of the Confirmation study and the pooled Discovery and Confirmation studies (reported in our Tables 2 and 3, respectively [2], and Brown et al.’s Table 3 [1]). This discrepancy in statistical power between Brown et al.’s selective reanalyses (reported in their Table 4) and a more complete analysis (replicated in their Table 3) is evident in the larger Standard Errors (SE) in their Table 4 versus Table 3 [1].

In their previous critique of our 2013 report [4] on gene expression correlates of well-being, Brown et al. [5] argued for the replication of findings in additional samples using mixed effect linear model analyses. Such data are now available from two new samples with 229 new participants, and results continue to indicate a significant inverse relationship between eudaimonic well-being and gene expression. Brown et al.’s claims of statistical instability rely on selective omission of these new data, which comprise 75% of the data presented in our 2015 PLoS ONE report.

Acknowledgments

The author wishes to thank Steve W. Cole for valuable contributions to this Comment.

Author Contributions

  1. Conceptualization: BLF.
  2. Formal analysis: BLF.
  3. Writing - original draft: BLF.
  4. Writing - review & editing: BLF.

References

  1. 1. Brown NJL, MacDonald DA, Samanta MP, Friedman HL, & Coyne JC (2016) More questions than answers: Continued Critical Reanalysis of Fredrickson et al.’s studies of genomics and well-being. PLoS ONE pmid:27270924
  2. 2. Fredrickson BL, Grewen KM, Algoe SB, Firestine AM, Arevalo JMG, Ma J, Cole SW (2015) Psychological well-being and the human conserved transcriptional response to adversity. PLoS ONE 10(3): e0121839. pmid:25811656
  3. 3. McCulloch CE, Searle SR, Neuhaus JM (2008) Generalized, linear, and mixed models. Hoboken NJ: John Wiley & Sons.
  4. 4. Fredrickson BL, Grewen KM, Coffey KA, Algoe SB, Firestine AM, Arevalo JM, Ma J, Cole SW (2013) A functional genomic perspective on human well-being. Proc Natl Acad Sci U S A 110: 13684–13689. pmid:23898182
  5. 5. Brown NJ, MacDonald DA, Samanta MP, Friedman HL, Coyne JC (2014) A critical reanalysis of the relationship between genomics and well-being. Proc Natl Acad Sci U S A