scholarly journals Evaluating the influence of action- and subject-specific factors on chimpanzee action copying

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alba Motes-Rodrigo ◽  
Roger Mundry ◽  
Josep Call ◽  
Claudio Tennie
Keyword(s):  
Observational Study ◽  
Power Analysis ◽  
Statistical Power ◽  
Simulated Data ◽  
Great Apes ◽  
Human Culture ◽  
Subject Specific ◽  
Specific Factors ◽  
Spontaneous Imitation ◽  
Sufficient Statistical Power

The ability to imitate has been deemed crucial for the emergence of human culture. Although non-human animals also possess culture, the acquisition mechanisms underlying behavioural variation between populations in other species is still under debate. It is especially controversial whether great apes can spontaneously imitate. Action- and subject-specific factors have been suggested to influence the likelihood of an action to be imitated. However, few studies have jointly tested these hypotheses. Just one study to date has reported spontaneous imitation in chimpanzees (Persson et al . 2017 Primates 59 , 19–29), although important methodological limitations were not accounted for. Here, we present a study in which we (i) replicate the above-mentioned study addressing their limitations in an observational study of human–chimpanzee imitation; and (ii) aim to test the influence of action- and subject-specific factors on action copying in chimpanzees by providing human demonstrations of multiple actions to chimpanzees of varying rearing background. To properly address our second aim, we conducted a preparatory power analysis using simulated data. Contrary to Persson et al .'s study, we found extremely low rates of spontaneous chimpanzee imitation and we did not find enough cases of action matching to be able to apply our planned model with sufficient statistical power. We discuss possible factors explaining the lack of observed action matching in our experiments compared with previous studies.

scholarly journals Towards a simplified justification of the chosen sample size

2021 ◽  
Author(s):  
Nick J. Broers ◽  
Henry Otgaar
Keyword(s):  
Sample Size ◽  
Effect Size ◽  
Power Analysis ◽  
Statistical Power ◽  
Minimal Effect ◽  
Expected Effect ◽  
Sufficient Statistical Power

Since the early work of Cohen (1962) psychological researchers have become aware of the importance of doing a power analysis to ensure that the predicted effect will be detectable with sufficient statistical power. APA guidelines require researchers to provide a justification of the chosen sample size with reference to the expected effect size; an expectation that should be based on previous research. However, we argue that a credible estimate of an expected effect size is only reasonable under two conditions: either the new study forms a direct replication of earlier work or the outcome scale makes use of meaningful and familiar units that allow for the quantification of a minimal effect of psychological interest. In practice neither of these conditions is usually met. We propose a different rationale for a power analysis that will ensure that researchers will be able to justify their sample size as meaningful and adequate.

scholarly journals Association between preoperative evaluation with lung ultrasound and outcome in frail elderly patients undergoing orthopedic surgery for hip fractures: study protocol for an Italian multicenter observational prospective study (LUSHIP)

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Luigi Vetrugno ◽  
Enrico Boero ◽  
Elena Bignami ◽  
Andrea Cortegiani ◽  
Santi Maurizio Raineri ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Postoperative Complications ◽  
Observational Study ◽  
Elderly Patients ◽  
Fracture Fixation ◽  
Frail Elderly ◽  
Statistical Power ◽  
Lung Ultrasound ◽  
Preoperative Evaluation ◽  
Cardiac Complications

Abstract Background Hip fracture is one of the most common orthopedic causes of hospital admission in frail elderly patients. Hip fracture fixation in this class of patients is considered a high-risk procedure. Preoperative physical examination, plasma natriuretic peptide levels (BNP, Pro-BNP), and cardiovascular scoring systems (ASA-PS, RCRI, NSQIP-MICA) have all been demonstrated to underestimate the risk of postoperative complications. We designed a prospective multicenter observational study to assess whether preoperative lung ultrasound examination can predict better postoperative events thanks to the additional information they provide in the form of “indirect” and “direct” cardiac and pulmonary lung ultrasound signs. Methods LUSHIP is an Italian multicenter prospective observational study. Patients will be recruited on a nation-wide scale in the 12 participating centers. Patients aged  >  65 years undergoing spinal anesthesia for hip fracture fixation will be enrolled. A lung ultrasound score (LUS) will be generated based on the examination of six areas of each lung and ascribing to each area one of the four recognized aeration patterns—each of which is assigned a subscore of 0, 1, 2, or 3. Thus, the total score will have the potential to range from a minimum of 0 to a maximum of 36. The association between 30-day postoperative complications of cardiac and/or pulmonary origin and the overall mortality will be studied. Considering the fact that cardiac complications in patients undergoing hip surgery occur in approx. 30% of cases, to achieve 80% statistical power, we will need a sample size of 877 patients considering a relative risk of 1.5. Conclusions Lung ultrasound (LU), as a tool within the anesthesiologist’s armamentarium, is becoming increasingly widespread, and its use in the preoperative setting is also starting to become more common. Should the study demonstrate the ability of LU to predict postoperative cardiac and pulmonary complications in hip fracture patients, a randomized clinical trial will be designed with the scope of improving patient outcome. Trial registration ClinicalTrials.gov, NCT04074876. Registered on August 30, 2019.

Sensitivity of male reproductive endpoints in nonhuman primate toxicity studies: A statistical power analysis

2013 ◽  
Vol 41 ◽  
pp. 67-72 ◽  
Author(s):  
G.D. Cappon ◽  
D. Potter ◽  
M.E. Hurtt ◽  
G.F. Weinbauer ◽  
C.M. Luetjens ◽  
...  
Keyword(s):  
Nonhuman Primate ◽  
Power Analysis ◽  
Statistical Power ◽  
Statistical Power Analysis ◽  
Toxicity Studies

Statistical power analysis for one-way analysis of variance: A computer program

1990 ◽  
Vol 22 (3) ◽  
pp. 271-282 ◽  
Author(s):  
Michael Borenstein ◽  
Jacob Cohen ◽  
Hannah R. Rothstein ◽  
Simcha Pollack ◽  
John M. Kane
Keyword(s):  
Computer Program ◽  
Analysis Of Variance ◽  
Power Analysis ◽  
Statistical Power ◽  
Statistical Power Analysis

Statistical Power Analysis can Improve Fisheries Research and Management

1990 ◽  
Vol 47 (1) ◽  
pp. 2-15 ◽  
Author(s):  
Randall M. Peterman
Keyword(s):  
Sample Size ◽  
Power Analysis ◽  
Statistical Power ◽  
Small Sample Size ◽  
Industrial Effluent ◽  
Small Sample ◽  
Detectable Effect ◽  
Type Ii ◽  
Sampling Variability ◽  
Statistical Power Analysis

Ninety-eight percent of recently surveyed papers in fisheries and aquatic sciences that did not reject some null hypothesis (H0) failed to report β, the probability of making a type II error (not rejecting H0 when it should have been), or statistical power (1 – β). However, 52% of those papers drew conclusions as if H0 were true. A false H0 could have been missed because of a low-power experiment, caused by small sample size or large sampling variability. Costs of type II errors can be large (for example, for cases that fail to detect harmful effects of some industrial effluent or a significant effect of fishing on stock depletion). Past statistical power analyses show that abundance estimation techniques usually have high β and that only large effects are detectable. I review relationships among β, power, detectable effect size, sample size, and sampling variability. I show how statistical power analysis can help interpret past results and improve designs of future experiments, impact assessments, and management regulations. I make recommendations for researchers and decision makers, including routine application of power analysis, more cautious management, and reversal of the burden of proof to put it on industry, not management agencies.

Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly

NeuroImage ◽  
2015 ◽  
Vol 108 ◽  
pp. 95-109 ◽  
Author(s):  
Franziskus Liem ◽  
Susan Mérillat ◽  
Ladina Bezzola ◽  
Sarah Hirsiger ◽  
Michel Philipp ◽  
...  
Keyword(s):  
Power Analysis ◽  
Statistical Power ◽  
Statistical Power Analysis ◽  
Large Sample ◽  
Healthy Elderly

Differences in Lost Letter Responses from a Seaside City

2001 ◽  
Vol 88 (3_suppl) ◽  
pp. 1194-1198 ◽  
Author(s):  
F. Stephen Bridges ◽  
C. Bennett Williamson ◽  
Donna Rae Jarvis
Keyword(s):  
Power Analysis ◽  
Statistical Power ◽  
Power Level ◽  
Effect Sizes ◽  
Gay And Lesbian ◽  
Rates Of Return ◽  
Florida Panhandle

Of 75 letters “lost” in the Florida Panhandle, 33 (44%) were returned in the mail by the finders (the altruistic response). Addressees' affiliations were significantly associated with different rates of return; fewer emotive Intercontinental Gay and Lesbian Outdoors Organization addressees were returned than nonemotive ones. The technique for power analysis by Gillett (1996) was applied to data from an earlier study and indicated our sample of 75 subjects would still yield a desired power level, i.e., 80, for the likely effect sizes. Statistical power was .83, and the effect was medium in size at .34.

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