Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Recent reviews suggest that, like much of the psychological literature, research studies using laboratory aggression paradigms tend to be underpowered to reliably locate commonly observed effect sizes (e.g., r = ~.10-.20, Cohen's d = ~0.20-0.40). In an effort to counter this trend, we provide a "power primer" that laboratory aggression researchers can use as a resource when planning studies using this methodology. Using simulation-based power analyses and effect size estimates derived from recent literature reviews, we provide sample size recommendations based on type of research question (e.g., main effect vs. two-way vs. three-way interactions) and correlations among predictors. Results highlight the large number of participants that must be recruited to reach acceptable (~80%) power, especially for tests of interactions where the recommended sample sizes far exceed those typically employed in this literature. These discrepancies are so substantial that we urge laboratory aggression researchers to consider a moratorium on tests of three-way interactions. Although our results use estimates from the laboratory aggression literature, we believe they are generalizable to other lines of research using behavioral tasks, as well as psychological science more broadly. We close by offering a series of best practice recommendations and reiterating long-standing calls for attention to statistical power as a basic element of study planning.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980114 | PMC |
http://dx.doi.org/10.1002/ab.21996 | DOI Listing |
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