Exploring power in response inhibition tasks using the bootstrap: The impact of number of participants, number of trials, effect magnitude, and study design

2019 ◽  
Author(s):  
Curtis David Von Gunten ◽  
Bruce D Bartholow
Keyword(s):  
Study Design ◽  
Effect Size ◽  
Statistical Power ◽  
Bootstrap Sampling ◽  
Reliable Measure ◽  
Internal Reliability ◽  
The Impact ◽  
Power Analyses ◽  
Effect Magnitude

A primary psychometric concern with laboratory-based inhibition tasks has been their reliability. However, a reliable measure may not be necessary or sufficient for reliably detecting effects (statistical power). The current study used a bootstrap sampling approach to systematically examine how the number of participants, the number of trials, the magnitude of an effect, and study design (between- vs. within-subject) jointly contribute to power in five commonly used inhibition tasks. The results demonstrate the shortcomings of relying solely on measurement reliability when determining the number of trials to use in an inhibition task: high internal reliability can be accompanied with low power and low reliability can be accompanied with high power. For instance, adding additional trials once sufficient reliability has been reached can result in large gains in power. The dissociation between reliability and power was particularly apparent in between-subject designs where the number of participants contributed greatly to power but little to reliability, and where the number of trials contributed greatly to reliability but only modestly (depending on the task) to power. For between-subject designs, the probability of detecting small-to-medium-sized effects with 150 participants (total) was generally less than 55%. However, effect size was positively associated with number of trials. Thus, researchers have some control over effect size and this needs to be considered when conducting power analyses using analytic methods that take such effect sizes as an argument. Results are discussed in the context of recent claims regarding the role of inhibition tasks in experimental and individual difference designs.

scholarly journals Strength of functional signature correlates with effect size in autism

2016 ◽  
Author(s):  
Sara Ballouz ◽  
Jesse Gillis
Keyword(s):  
Study Design ◽  
Effect Size ◽  
Statistical Power ◽  
Fragile X ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Protein Interaction Data ◽  
Functional Convergence ◽  
Study Designs ◽  
The Impact

AbstractBackgroundDisagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach.MethodIn this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence.ResultsWe detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (FDR<0.01), many in areas researchers have targeted based on different reasoning, such as the fragile X mental retardation protein (FMRP) interactor enrichment (FDR 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein-protein interaction data is heavily confounded with study design, arising readily in control data.ConclusionsWe see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.

scholarly journals A Multi-faceted Mess: A Review of Statistical Power Analysis in Psychology Journal Articles

2019 ◽  
Author(s):  
Rob Cribbie ◽  
Nataly Beribisky ◽  
Udi Alter
Keyword(s):  
Sample Size ◽  
Effect Size ◽  
Power Analysis ◽  
Statistical Power ◽  
Type I Error ◽  
A Priori ◽  
Type I ◽  
Specific Level ◽  
Maximum Sample Size ◽  
Power Analyses

Many bodies recommend that a sample planning procedure, such as traditional NHST a priori power analysis, is conducted during the planning stages of a study. Power analysis allows the researcher to estimate how many participants are required in order to detect a minimally meaningful effect size at a specific level of power and Type I error rate. However, there are several drawbacks to the procedure that render it “a mess.” Specifically, the identification of the minimally meaningful effect size is often difficult but unavoidable for conducting the procedure properly, the procedure is not precision oriented, and does not guide the researcher to collect as many participants as feasibly possible. In this study, we explore how these three theoretical issues are reflected in applied psychological research in order to better understand whether these issues are concerns in practice. To investigate how power analysis is currently used, this study reviewed the reporting of 443 power analyses in high impact psychology journals in 2016 and 2017. It was found that researchers rarely use the minimally meaningful effect size as a rationale for the chosen effect in a power analysis. Further, precision-based approaches and collecting the maximum sample size feasible are almost never used in tandem with power analyses. In light of these findings, we offer that researchers should focus on tools beyond traditional power analysis when sample planning, such as collecting the maximum sample size feasible.

scholarly journals Satisfaction of ottenders and non-attenders with their treatments at psychiatric out-patient clinics

1998 ◽  
Vol 22 (10) ◽  
pp. 612-615 ◽  
Author(s):  
Helen Killaspy ◽  
Julia Gledhill ◽  
Sube Banerjee
Keyword(s):  
Patient Satisfaction ◽  
Statistical Power ◽  
Important Determinant ◽  
Self Report ◽  
Financial Cost ◽  
Patient Dissatisfaction ◽  
Outpatient Appointments ◽  
The Impact

Aims and methodNon-attendance at psychiatric outpatient appointments has a substantial financial cost, and may also have clinical significance. To prevent non-attendance and formulate effective responses, its determinants need to be understood. Patient dissatisfaction with services has been suggested as a reason for non-attendance, we therefore investigated the role of patient satisfaction in attendance at psychiatric out-patients appointments. All patients booked for adult psychiatric out-patient follow-up appointments in a three-month period were studied using a brief, self-report questionnaire.ResultsSixty-three per cent (340/538) of offenders and 54% (118/219) of non-attenders responded. Responders expressed high levels of satisfaction with their treatment (92% offenders, 91% non-attenders) and with the service (96% attenders 92% non-attenders). Despite adequate statistical power, there were no statistically significant differences in satisfaction between the two groups.Clinical implicationsIn conclusion, patient satisfaction with psychiatric out-patient care was reported to be relatively high and did not seem to be an important determinant of non-attendance. Further work is needed to determine the impact of variables such as relapse and social disorganisation on attendance.

Abstract P226: Decreasing Cardiovascular Risk via Hypertriglyceridemia Treatment: The Impact of Medical Education on Physician Understanding of the Role of Omega-3 Fatty Acids

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Amy Larkin ◽  
George Boutsalis ◽  
Michael LaCouture
Keyword(s):  
Fatty Acids ◽  
Medical Education ◽  
Effect Size ◽  
Further Education ◽  
Omega 3 Fatty Acids ◽  
Omega 3 ◽  
The Impact ◽  
Post Assessment ◽  
Assessment Questions

Introduction: Triglycerides, although lacking the strong atherogenic potential of LDL-C, are an independent risk factor for cardiovascular disease (CVD), as demonstrated by the correlation between hypertriglyceridemia and cardiovascular (CV) death, CV events, and myocardial infarction. The impact of continuing medical education (CME) on improving the knowledge and competence of cardiologists in treating hypertriglyceridemia with omega-3 fatty acids was measured. Methods: Cardiologists in the US who treat patients with hypertriglyceridemia participated in an online CME activity on the role of omega-3 fatty acids in treating hypertriglyceridemia and the differences between available formulations. The educational impact was assessed using linked pre- and post-assessment questions, and participants were classified into one of 3 learning categories: improved learners (incorrect pre, correct post), reinforced learners (correct pre and post), and unaffected learners (incorrect pre and post). The educational effect size was calculated using Cohen's d formula. Results: A total of 169 cardiologists participated in the CME activity, completed the pre- and post-assessment, and were included in the analysis. Comparison of pre- and post-assessment responses for each individual question demonstrated a statistically significant improvement in knowledge and competence among cardiologists ( P <.05). After completion of the CME activity, correct responses on post-assessment questions increased between 25% to 158% across all questions compared to pre-assessment responses, with an overall large effect size of 1.065 (Small effect ,<0.4; intermediate effect, 0.4-0.8; large effect, >0.8). Between 17% and 51% of participants showed improvement in understanding individual learning concepts; these concepts were reinforced in 18% to 28% of participants. Improvement was demonstrated in understanding recent American College of Cardiology (ACC)/American Heart Association (AHA) guideline recommendations on the treatment of hypertriglyceridemia. There was a need for further education in understanding the mechanism of action of omega-3 fatty acids, the differences between prescription and supplement forms of omega-3 fatty acids, and the pharmacodynamic differences between the different formulations of omega-3 fatty acids. Conclusion: This study demonstrated the success of a targeted educational intervention on improving the knowledge and competence of US cardiologists on the role of omega-3 fatty acids to treat hypertriglyceridemia and reduce CVD. However, the need for additional education was also demonstrated among cardiologists with regard to understanding the different omega-3 fatty acid formulations and their mechanisms of action in order to effectively use these agents.

scholarly journals Population Pharmacokinetic Assessment of the Effect of Food on Piperaquine Bioavailability in Patients with Uncomplicated Malaria

2014 ◽  
Vol 58 (4) ◽  
pp. 2052-2058 ◽  
Author(s):  
Joel Tarning ◽  
Niklas Lindegardh ◽  
Khin Maung Lwin ◽  
Anna Annerberg ◽  
Lily Kiricharoen ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Study Design ◽  
Statistical Power ◽  
Mixed Effects ◽  
Distribution Model ◽  
Population Pharmacokinetic ◽  
Final Model ◽  
Content Type ◽  
Mixed Effects Modeling ◽  
The Impact

ABSTRACTPreviously published literature reports various impacts of food on the oral bioavailability of piperaquine. The aim of this study was to use a population modeling approach to investigate the impact of concomitant intake of a small amount of food on piperaquine pharmacokinetics. This was an open, randomized comparison of piperaquine pharmacokinetics when administered as a fixed oral formulation once daily for 3 days with (n= 15) and without (n= 15) concomitant food to patients with uncomplicatedPlasmodium falciparummalaria in Thailand. Nonlinear mixed-effects modeling was used to characterize the pharmacokinetics of piperaquine and the influence of concomitant food intake. A modified Monte Carlo mapped power approach was applied to evaluate the relationship between statistical power and various degrees of covariate effect sizes of the given study design. Piperaquine population pharmacokinetics were described well in fasting and fed patients by a three-compartment distribution model with flexible absorption. The final model showed a 25% increase in relative bioavailability per dose occasion during recovery from malaria but demonstrated no clinical impact of concomitant intake of a low-fat meal. Body weight and age were both significant covariates in the final model. The novel power approach concluded that the study was adequately powered to detect a food effect of at least 35%. This modified Monte Carlo mapped power approach may be a useful tool for evaluating the power to detect true covariate effects in mixed-effects modeling and a given study design. A small amount of food does not affect piperaquine absorption significantly in acute malaria.

Defining Replication in Gene × Environnment Interaction Research: The Risk of Spurious Associations

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
M. Munafo
Keyword(s):  
Statistical Power ◽  
Twin Studies ◽  
Weight Of Evidence ◽  
Environmental Interactions ◽  
Original Report ◽  
Definition Of ◽  
The Impact ◽  
Interaction Research ◽  
Relevant Factors

There has been considerable interest in recent years in the investigation of the role of gene x environment (G x E) interactions in aetiology of psychiatric disorders. While the fact that genetic effects may moderate the effects of environmental exposure is widely accepted, and supported by family and twin studies, there is controversy regarding the degree of evidence for specific G x E interactions reported in the literature. Here it is argued that examples of environmental interactions with genes identified at the molecular level are not as well established as widely believed.A number of relevant factors influencing the weight of evidence for specific G x E interactions will be discussed, including the degree of stringency employed in the definition of “replication”, the impact of different statistical models used to test for interactions, and the statistical power of individual studies. It is concluded that in only a minority of studies is a replication reported that is qualitatively comparable to that in the original report. Given reasonable assumptions regarding likely genetic and environmental effects, simulations indicate that published studies are most likely underpowered, suggesting that positive results for widely reported G x E interactions may be compatible with chance findings.

scholarly journals Sample size, sample size planning, and the impact of study context: systematic review and recommendations by the example of psychological depression treatment

2021 ◽  
pp. 1-7
Author(s):  
Raphael Schuster ◽  
Tim Kaiser ◽  
Yannik Terhorst ◽  
Eva Maria Messner ◽  
Lucia-Maria Strohmeier ◽  
...  
Keyword(s):  
Sample Size ◽  
Study Design ◽  
Statistical Power ◽  
Face To Face ◽  
Internet Interventions ◽  
Study Planning ◽  
Sample Size Planning ◽  
Highly Correlated ◽  
Study Context ◽  
The Impact

Abstract Background Sample size planning (SSP) is vital for efficient studies that yield reliable outcomes. Hence, guidelines, emphasize the importance of SSP. The present study investigates the practice of SSP in current trials for depression. Methods Seventy-eight randomized controlled trials published between 2013 and 2017 were examined. Impact of study design (e.g. number of randomized conditions) and study context (e.g. funding) on sample size was analyzed using multiple regression. Results Overall, sample size during pre-registration, during SSP, and in published articles was highly correlated (r's ≥ 0.887). Simultaneously, only 7–18% of explained variance related to study design (p = 0.055–0.155). This proportion increased to 30–42% by adding study context (p = 0.002–0.005). The median sample size was N = 106, with higher numbers for internet interventions (N = 181; p = 0.021) compared to face-to-face therapy. In total, 59% of studies included SSP, with 28% providing basic determinants and 8–10% providing information for comprehensible SSP. Expected effect sizes exhibited a sharp peak at d = 0.5. Depending on the definition, 10.2–20.4% implemented intense assessment to improve statistical power. Conclusions Findings suggest that investigators achieve their determined sample size and pre-registration rates are increasing. During study planning, however, study context appears more important than study design. Study context, therefore, needs to be emphasized in the present discussion, as it can help understand the relatively stable trial numbers of the past decades. Acknowledging this situation, indications exist that digital psychiatry (e.g. Internet interventions or intense assessment) can help to mitigate the challenge of underpowered studies. The article includes a short guide for efficient study planning.

Intergroup Threat and Outgroup Attitudes

2013 ◽  
Vol 44 (5) ◽  
pp. 311-319 ◽  
Author(s):  
Marco Brambilla ◽  
David A. Butz
Keyword(s):  
Gay Men ◽  
Social Group ◽  
Welfare Recipients ◽  
Intergroup Attitudes ◽  
Social Policies ◽  
Intergroup Threat ◽  
Economic Threat ◽  
The Impact ◽  
General Climate

Two studies examined the impact of macrolevel symbolic threat on intergroup attitudes. In Study 1 (N = 71), participants exposed to a macrosymbolic threat (vs. nonsymbolic threat and neutral topic) reported less support toward social policies concerning gay men, an outgroup whose stereotypes implies a threat to values, but not toward welfare recipients, a social group whose stereotypes do not imply a threat to values. Study 2 (N = 78) showed that, whereas macrolevel symbolic threat led to less favorable attitudes toward gay men, macroeconomic threat led to less favorable attitudes toward Asians, an outgroup whose stereotypes imply an economic threat. These findings are discussed in terms of their implications for understanding the role of a general climate of threat in shaping intergroup attitudes.

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