15938 Tildrakizumab efficacy by metabolic syndrome status in psoriasis: Post hoc analysis of 3-year data from the phase 3 reSURFACE 1 study
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Post-hoc analysis
Post hoc
Interleukin-23
Using a hypothetical scenario typifying the experience that authors have when submitting manuscripts that report results of negative clinical trials, the pitfalls of a post hoc analysis are illustrated. We used the same scenario to explain how confidence intervals are used in interpreting results of clinical trials. We showed that confidence intervals better inform readers about the possibility of an inadequate sample size than do post hoc power calculations.
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Abstract This paper illustrates the use of a Scheffé-like multivariate post hoc procedure known as the Roy-Bose or simultaneous confidence interval procedure. This method is contrasted with the use of Bonferroni or planned linear combinations for the one- and two-sample cases. The Roy-Bose procedure also is compared to the more frequently employed univariate F tests for post hoc analysis.
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Post-hoc analysis
Univariate
Bonferroni correction
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Scheffé's method
Multiple comparisons problem
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Scheffé’s test ( Scheffé, 1953 ), which is commonly used to conduct post hoc contrasts among k group means, is unnecessarily conservative because it guards against an infinite number of potential post hoc contrasts when only a small set would ever be of interest to a researcher. This paper identifies a set of post hoc contrasts based on subsets of the treatment groups and simulates critical values from the appropriate multivariate F-distribution to be used in place of those associated with Scheffé’s test. The proposed method and its critical values provide a uniformly more powerful post hoc procedure.
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The purpose of this paper is to present basic characteristics and highlight the differences between post hoc tests, as well as to show their application on concrete data of the research conducted. The said tests are applied on data obtained in the research which found evidence of 240 Serbian hotel ratings, given by their 71,700 guests. Each guest rated: cleanliness, comfort, location, facilities, staff, value for money, and free Wi-Fi in the hotel. A difference in ratings in relation to hotel category was observed and explained using several post hoc tests. The use of those tests is made much easier with the development of numerous statistical software packages. Therefore, clearly differentiating each of the tests allows one to select the most appropriate test in the research process, according to the type of data and research objectives. The paper presents the tests used when one-way analysis of variance, which is a method frequently used in statistical processing of experimental data, finds evidence of the existence of statistically significant differences in values of arithmetic mean in groups of data observed. The task of post hoc tests is to determine which group of data leads to the difference observed. Tests thus presented here are: the Fisher LSD, the Tukey HSD, the Bonferroni , the Newman-Keuls, the Dunnett and the Scheffe test.
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Serbian
Bonferroni correction
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Abstract Aim To assess the relationship between HbA1c and body weight reductions with tirzepatide treatment (5, 10 or 15 mg). Materials and Methods HbA1c and body weight data at 40 weeks (SURPASS‐1, ‐2 and ‐5) and 52 weeks (SURPASS‐3 and ‐4) were analysed by trial. Results Across the SURPASS clinical trials, HbA1c reductions from baseline were observed in 96%‐99%, 98%‐99% and 94%‐99% of participants treated with tirzepatide 5, 10 and 15 mg, respectively. Moreover, 87%‐94%, 88%‐95% and 88%‐97% of participants, respectively, experienced weight loss associated with HbA1c reductions. Statistically significant associations (correlation coefficients ranging from 0.1438 to 0.3130 across studies; P ≤ .038) between HbA1c and body weight changes were observed with tirzepatide in SURPASS‐2, ‐3, ‐4 (all doses) and ‐5 (tirzepatide 5 mg only). Conclusions In this post hoc analysis, consistent reductions in both HbA1c and body weight were observed in most participants treated with tirzepatide at doses of 5, 10 or 15 mg. A statistically significant but modest association between HbA1c and body weight change was observed in SURPASS‐2, SURPASS‐3 and SURPASS‐4, suggesting that both weight‐independent and weight‐dependent mechanisms are responsible for the tirzepatide‐induced improvement in glycaemic control.
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Abstract Review of nursing research literature revealed that post hoc comparisons of mean differences were not consistently reported, although their use was warranted. This paper describes the critical features of post hoc procedures and offers guidelines for selecting one method over another. Particular attention is given to how various procedures control Type 1 error. Selection of post hoc procedures considering the investigator's desire for control of Type 1 and Type 2 error also is presented.
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The online support of IBM SPSS proposes that users alter the syntax when performing post-hoc analyses for interaction effects of ANOVA tests. Other authors also suggest altering the syntax when performing GEE analyses. This being done, the number of possible comparisons (k value) is also altered, therefore influencing the results from statistical tests that k is a component of the formula, such as repeated measures-ANOVA and Bonferroni post-hoc of ANOVA and GEE. This alteration also exacerbates type I error, producing erroneous results and conferring potential misinterpretations of data. Reasoning from this, the purpose of this paper is to report the misuse and improper handling of syntax for ANOVAs and GEE post-hoc analyses in SPSS and to illustrate its consequences on statistical results and data interpretation.
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Post-hoc analysis
Bonferroni correction
Gee
Repeated measures design
Statistical Analysis
Analysis of covariance
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