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Survival Analysis
Published in Trevor F. Cox, Medical Statistics for Cancer Studies, 2022
A common multiple comparison method is the Bonferroni method, which uses a significance level of for each test. To make the Bonferroni correction for each test made, simply multiply the p-value, p, obtained for each test by N, to give the adjusted p-value, for the test. Then compare this with the significance level, α. The Bonferroni correction is rather conservative and only cautiously rejects a null-hypothesis.
Statistical Methods for Big Data
Published in Ching-Yu Cheng, Tien Yin Wong, Ophthalmic Epidemiology, 2022
Emmanuel Kemel, Alexandre Thiery, Simon Nusinovici
Furthermore, testing many predictors can lead to multiple testing issues. The repeated hypothesis testing is likely to result in a high number of false positives. Two methods are commonly used to correct for that issue by applying a form of p-value correction: Bonferroni correction or the false discovery rate (FDR) (14). Moreover, increasing the number of predictors increases the risk of multicollinearity.
Dual Energy Computed Tomography for Lung Cancer Diagnosis and Characterization
Published in Ayman El-Baz, Jasjit S. Suri, Lung Imaging and CADx, 2019
Victor Gonzalez-Perez, Estanislao Arana, David Moratal
Table 3.10 summarizes the outcomes of Mann-Whitney U test in the differentiation of tumor necrotic status. In order to determine the statistically significant value, the Bonferroni correction was performed: p = 0.05/18 = 0.0028.
The effects of spinal stabilization exercises in patients with myasthenia gravis: a randomized crossover study
Published in Disability and Rehabilitation, 2022
Ali Naim Ceren, Yeliz Salcı, Ayla Fil Balkan, Ebru Çalık Kütükçü, Kadriye Armutlu, Sevim Erdem Özdamar
Mann-Whitney U Test and Chi-square test were used to compare the clinical and demographic characteristics of the patients. Due to the small sample size, non-parametric tests were used. The washout effect was evaluated with the Wilcoxon Test between the first (pre-first program) and third (pre-second program) evaluations. The data of the groups were combined, as it was seen that there was a washout effect in all data, and new groups were created according to the exercise programs. Wilcoxon Test was used again to evaluate the changes of exercise groups over time. The Mann-Whitney U Test was used to see the difference between exercises. The significance value was accepted as p < .05. In this study, although fatigue was determined as the primary outcome measure, muscle strength, respiratory functions, and functional capacity assessments were also important outcome measures. When examining the effects of an intervention on more than one outcome, false positive significant results can be found. This error probability is named as the familywise error rate (FWER). A multiple correction method is required to control the FWER [29]. In this study, the Bonferroni correction was used for controlling the FWER. The significance level (α) was split as the number of important outcome measures (k) and each outcome measure was tested at level α/k (.05/4) =0.0125. Statistical analyses were performed using IBM SPSS 20.0 for Mac software (SPSS Inc., Chicago, IL, USA).
Influence of HLA Class II Alleles and DRB1-DQB1 Haplotypes on Rheumatoid Arthritis Susceptibility and Autoantibody Status in the Chinese Han Population
Published in Immunological Investigations, 2022
Xin Wan, Ying Wang, Peipei Jin, Ju Zhang, Liu Liu, Zhangfei Wang, Yue Hu
The frequencies of HLA-DRB1~ DQB1 haplotypes were compared between RA patients and control group. As shown in Table 5, strong positive association of HLA-DRB1*04~ DQB1*04 and HLA-DRB1*10~ DQB1*05 haplotypes with RA susceptibility were maintained after correction of multiple comparisons. Analysis of haplotypes showed a specifically higher frequency of the HLA-DRB1*04:05:01~ DQB1*04:01:01 (11.6% vs. 3.3%, Pc = 0.007, OR = 3.81, 95% CI = 1.70–8.51) and HLA-DRB1*10:01:01~ DQB1*05:01:01 (6.4% vs. 0.4%, Pc = 0.003, OR = 16.34, 95% CI = 2.15–124.30) in RA patients compared with controls. The frequencies of HLA-DRB1*04~ DQB1*03 (11.6% vs. 5.8%, Pc = 0.36) and HLA-DRB1*16~ DQB1*05 (3.2% vs. 0.4%, Pc = 0.53) were higher while HLA-DRB1*13~ DQB1*06 (2.0% vs. 7.1%, Pc = 0.112) was lower in RA patients than in controls. However, these differences cannot be considered as statistically significant after Bonferroni correction for multiple testing.
Anthropometric, biochemical and clinical parameters in climacteric yoga practitioners
Published in Climacteric, 2022
L. A. Cota e Souza, A. A. Lima
All data were entered twice and reviewed for consistency (EpiData – Comprehensive Data Management and Basic Statistical Analysis System; EpiData Association, Odense, Denmark). We performed analyses using the Statistical Package for Social Sciences software (IBM SPSS Statistics for Windows, Version 20.0; IBM Corp., Armonk, NY, USA). We compared categorical variables using the Pearson chi-square test and tested the normality of continuous variables using the Kolmogorov–Smirnov test. Normal variables were reported as the mean ± standard deviation and compared using one-way analysis of variance. Non-parametric variables were reported as the median with first and third quartiles, and compared using the Kruskal–Wallis test. Bonferroni correction was used for multiple comparison. All statistical tests were significant at the level of 5%.