Donald R. Williams

Effects of intranasal oxytocin on symptoms of schizophrenia: A multivariate Bayesian meta-analysis

Schizophrenia is a heterogeneous disorder in which psychiatric symptoms are classified into two general subgroups-positive and negative symptoms. Current antipsychotic drugs are effective for treating positive symptoms, whereas negative symptoms are less responsive. Since the neuropeptide oxytocin (OT) has been shown to mediate social behavior in animals and humans, it has been used as an experimental therapeutic for treating schizophrenia and in particular negative symptoms which includes social deficits. Through eight randomized controlled trials (RCTs) and three meta-analyses, evidence for an effect of intranasal OT (IN-OT) has been inconsistent. We therefore conducted an updated meta-analysis that offers several advantages when compared to those done previously: (1) We used a multivariate analysis which allows for comparisons between symptoms and accounts for correlations between symptoms; (2) We controlled for baseline scores; (3) We used a fully Bayesian framework that allows for assessment of evidence in favor of the null hypothesis using Bayes factors; and (4) We addressed inconsistencies in the primary studies and previous meta-analyses. Eight RCTs (n=238) were included in the present study and we found that oxytocin did not improve any aspect of symptomology in schizophrenic patients and there was moderate evidence in favor of the null (no effect of oxytocin) for negative symptoms. Multivariate comparisons between symptom types revealed that oxytocin was not especially beneficial for treating negative symptoms. The effect size estimates were not moderated, publication bias was absent, and our estimates were robust to sensitivity analyses. These results suggest that IN-OT is not an effective therapeutic for schizophrenia.

Justify your alpha

In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.

Bayesian alternatives for common null-hypothesis significance tests in psychiatry: A non-technical guide using JASP

BackgroundDespite its popularity as an inferential framework, classical null hypothesis significance testing (NHST) has several restrictions. Bayesian analysis can be used to complement NHST, however, this approach has been underutilized largely due to a dearth of accessible software options. JASP is a recently developed open-source statistical package that facilitates both Bayesian and NHST analysis using a graphical interface. This article provides an applied introduction to Bayesian inference with Bayes factors using JASP.MethodsWe use JASP to compare and contrast Bayesian alternatives for several common classical null hypothesis significance tests: correlations, frequency distributions, t-tests, ANCOVAs, and ANOVAs. These examples are also used to illustrate the strengths and limitations of both NHST and Bayesian hypothesis testing.ResultsA comparison of NHST and Bayesian inferential frameworks demonstrates that Bayes factors can complement p-values by providing additional information for hypothesis testing. Namely, Bayes factors can quantify relative evidence for both alternative and null hypotheses. Moreover, the magnitude of this evidence can be presented as an easy-to-interpret odds ratio.ConclusionsWhile Bayesian analysis is by no means a new method, this type of statistical inference has been largely inaccessible for most psychiatry researchers. JASP provides a straightforward means of performing reproducible Bayesian hypothesis tests using a graphical “point and click” environment that will be familiar to researchers conversant with other graphical statistical packages, such as SPSS.

Bayes Factors From Pooled Data Are No Substitute for Bayesian Meta-Analysis: Commentary on Scheibehenne, Jamil, and Wagenmakers (2016)

Scheibehenne, Jamil, and Wagenmakers (2016; SJW) recently introduced Bayesian evidence synthesis (BES). They used it to combine evidence from seven published studies that examined the influence of ...

Between-litter variation in developmental studies of hormones and behavior: inflated false positives and diminished power

Developmental studies of hormones and behavior often include littermates-rodent siblings that share early-life experiences and genes. Due to between-litter variation (i.e., litter effects), the statistical assumption of independent observations is untenable. In two literatures-natural variation in maternal care and prenatal stress-entire litters are categorized based on maternal behavior or experimental condition. Here, we (1) review both literatures; (2) simulate false positive rates for commonly used statistical methods in each literature; and (3) characterize small sample performance of multilevel models (MLM) and generalized estimating equations (GEE). We found that the assumption of independence was routinely violated (>85%), false positives (α=0.05) exceeded nominal levels (up to 0.70), and power (1-β) rarely surpassed 0.80 (even for optimistic sample and effect sizes). Additionally, we show that MLMs and GEEs have adequate performance for common research designs. We discuss implications for the extant literature, the field of behavioral neuroendocrinology, and provide recommendations.

Data extraction and statistical errors: a quantitative critique of Gumley, Braehler, & Macbeth, (2014)

OBJECTIVE While oxytocin has been identified as having therapeutic properties for schizophrenia, the emerging evidence has been mixed which has resulted in meta-analytic reviews. We identified several errors in one such meta-analysis. Here, we highlight these errors, demonstrate the conclusions were incorrect, and state the importance of this report. METHODS We reproduced the methods of Gumley, Braehler, and Macbeth (), including: outcomes (positive, negative, and total symptoms, as well as general psychopathology) and meta-analytic estimates for fixed and random effect models. RESULTS Whereas Gumley, Braehler, and Macbeth () reported oxytocin had significant effects on three of four outcomes, we show that all effects were non-significant. CONCLUSIONS Based on these null results, we hope this report encourages a re-evaluation of intranasal oxytocin as a treatment for schizophrenia.