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Younas A. Beyond 'statistical significance': A nontechnical primer of Bayesian statistics and Bayes factors for health researchers. J Eval Clin Pract 2024. [PMID: 38825756 DOI: 10.1111/jep.14032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/14/2024] [Accepted: 05/16/2024] [Indexed: 06/04/2024]
Abstract
RATIONALE Hypothesis testing is integral to health research and is commonly completed through frequentist statistics focused on computing p values. p Values have been long criticized for offering limited information about the relationship of variables and strength of evidence concerning the plausibility, presence and certainty of associations among variables. Bayesian statistics is a potential alternative for inference-making. Despite emerging discussion on Bayesian statistics across various disciplines, the uptake of Bayesian statistics in health research is still limited. AIM To offer a primer on Bayesian statistics and Bayes factors for health researchers to gain preliminary knowledge of its use, application and interpretation in health research. METHODS Theoretical and empirical literature on Bayesian statistics and methods were used to develop this methodological primer. CONCLUSIONS Using Bayesian statistics in health research without a careful and complete understanding of its underlying philosophy and differences from frequentist testing, estimation and interpretation methods can result in similar ritualistic use as done for p values. IMPLICATIONS Health researchers should supplement frequentists statistics with Bayesian statistics when analysing research data. The overreliance on p values for clinical decisions making should be avoided. Bayes factors offer a more intuitive measure of assessing the strength of evidence for null and alternative hypothesis.
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Affiliation(s)
- Ahtisham Younas
- Memorial University of Newfoundland, St. John's, Newfoundland, Canada
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Arahmane H, Dumazert J, Barat E, Dautremer T, Carrel F, Dufour N, Michel M. Statistical approach for radioactivity detection: A brief review. JOURNAL OF ENVIRONMENTAL RADIOACTIVITY 2024; 272:107358. [PMID: 38142518 DOI: 10.1016/j.jenvrad.2023.107358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023]
Abstract
Radioactivity detection is a major research and development priority for many practical applications. Amongst the various technical challenges in this field is the need to carry out accurate low-level radioactivity measurements in the presence of a large fluctuations in the natural radiation background, while reducing the false alarm rates. The task becomes even more harder with high detection limits under low signal-to-background ratios. A detection method based on the statistical inference, following either a frequentist or a Bayesian paradigm, adopted to overcome these challenges as well as to ensure a reliable and accurate diagnosis with a competitive tradeoff between sensitivity, specificity and response time. With this respect, several research studies, addressing a range of applications from decommissioning and dismantling to homeland security, have been proposed. Our main goal in this paper is to present a succinct survey of these studies based on a frequentist and Bayesian approaches used to decision-making, uncertainty and risk evaluation, in the context of radioactive detection. In this prospect, a theoretical background of statistical frequentist and Bayesian inferences was presented. Then, a comparative study of both approaches was performed to determine the optimal approach in regards to accuracy and pros/cons. A case of study for low-level radioactivity detection in nuclear decommissioning operations was provided to validate the optimal approach. Results proved the efficiency and usefulness of Bayesian approach against frequentist one with respect to the most challenging scenarios in radiation detection applications.
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Affiliation(s)
- Hanan Arahmane
- Université Paris-Saclay, CEA, List, F-91120 Palaiseau, France.
| | | | - Eric Barat
- Université Paris-Saclay, CEA, List, F-91120 Palaiseau, France
| | | | | | | | - Maugan Michel
- Université Paris-Saclay, CEA, List, F-91120 Palaiseau, France
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Choi BM, Weinberger AH, Petersen N, Pang RD, DeVito EE, Bell ML, Allen AM. Association of e-Cigarette Use and Postpartum Depression: Pregnancy Risk Assessment Monitoring System 2016-2019. J Womens Health (Larchmt) 2024; 33:45-51. [PMID: 37944112 PMCID: PMC10794836 DOI: 10.1089/jwh.2023.0061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023] Open
Abstract
Background: Postpartum depression (PPD) is a prevalent public health concern. Combustible cigarette use is associated with increased risk of PPD. While electronic cigarette (e-cigarette) use during pregnancy is linked to increased risk of depressive symptoms during pregnancy, the relationship between e-cigarette use and PPD is not well understood. We sought to examine the association of e-cigarette use with PPD. Materials and Methods: Using Pregnancy Risk Assessment Monitoring System 2016-2019 data, unadjusted and adjusted logistic regression analyses for PPD were conducted via three analyses where e-cigarette use (any vs. none) was retrospectively self-reported (1) in past 2-year, (2) prepregnancy (i.e., 3 months before pregnancy), and (3) during pregnancy (i.e., last 3 months of pregnancy). We conducted an additional past 2-year e-cigarette use analysis excluding those who used combustible cigarette and/or hookah. Covariates included age, race, ethnicity, combustible cigarette, and/or hookah use, prenatal care during the last trimester, health insurance coverage during pregnancy, physical abuse during pregnancy, income, and survey type. Results: Only unadjusted odds ratios from past 2-year e-cigarette use (1.63, 95% confidence interval [CI]: 1.42-1.87) and past 2-year e-cigarette use excluding individuals with cigarette and/or hookah use (1.78, 95% CI: 1.30-2.38) were statistically associated with PPD. No adjusted analyses were statistically significant. Conclusion: Any e-cigarette use, as compared to no use, does not appear to be an independent risk factor of PPD, though it may be a useful clinical marker of increased risk of PPD. Future studies are warranted to advance our knowledge of impact of e-cigarette use on PPD.
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Affiliation(s)
- Briana M. Choi
- Center for Health Outcomes and PharmacoEconomic Research, R. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA
| | - Andrea H. Weinberger
- Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, New York, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Nicole Petersen
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Raina D. Pang
- Department of Population and Public Health Sciences and University of Southern California, Los Angeles, California, USA
- Department of Psychology, University of Southern California, Los Angeles, California, USA
| | - Elise E. DeVito
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Melanie L. Bell
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA
| | - Alicia M. Allen
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA
- Department of Family and Community Medicine, College of Medicine, University of Arizona, Tucson, Arizona, USA
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Baig SA. Bayesian inference: Parameter estimation for inference in small samples. Nicotine Tob Res 2021; 24:937-941. [PMID: 34679175 DOI: 10.1093/ntr/ntab221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 10/19/2021] [Indexed: 11/14/2022]
Affiliation(s)
- Sabeeh A Baig
- Center for Tobacco Products, Food and Drug Administration, Document Control Center, Silver Spring, MD
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Baig SA. Bayesian inference: Evaluating replication attempts with Bayes factors. Nicotine Tob Res 2021; 24:626-629. [PMID: 34673977 DOI: 10.1093/ntr/ntab219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 10/19/2021] [Indexed: 11/12/2022]
Affiliation(s)
- Sabeeh A Baig
- Center for Tobacco Products, Food and Drug Administration, Document Control Center, 10903 New Hampshire Avenue, Building 71, Room G335, Silver Spring, MD
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Garnier-Villarreal M, Pinto D, Mummidisetty CK, Jayaraman A, Tefertiller C, Charlifue S, Taylor HB, Chang SH, McCombs N, Furbish CL, Field-Fote EC, Heinemann AW. Predicting Duration of Outpatient Physical Therapy Episodes for Individuals with Spinal Cord Injury Based on Locomotor Training Strategy. Arch Phys Med Rehabil 2021; 103:665-675. [PMID: 34648804 DOI: 10.1016/j.apmr.2021.07.815] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/17/2021] [Accepted: 07/02/2021] [Indexed: 01/18/2023]
Abstract
OBJECTIVE To characterize individuals with spinal cord injuries (SCI) who use outpatient physical therapy or community wellness services for locomotor training and predict the duration of services, controlling for demographic, injury, quality of life, and service and financial characteristics. We explore how the duration of services is related to locomotor strategy. DESIGN Observational study of participants at 4 SCI Model Systems centers with survival. Weibull regression model to predict the duration of services. SETTING Rehabilitation and community wellness facilities at 4 SCI Model Systems centers. PARTICIPANTS Eligibility criteria were SCI or dysfunction resulting in motor impairment and the use of physical therapy or community wellness programs for locomotor/gait training. We excluded those who did not complete training or who experienced a disruption in training greater than 45 days. Our sample included 62 participants in conventional therapy and 37 participants in robotic exoskeleton training. INTERVENTIONS Outpatient physical therapy or community wellness services for locomotor/gait training. MAIN OUTCOME MEASURES SCI characteristics (level and completeness of injury) and the duration of services from medical records. Self-reported perceptions of SCI consequences using the SCI-Functional Index for basic mobility and SCI-Quality of Life measurement system for bowel difficulties, bladder difficulties, and pain interference. RESULTS After controlling for predictors, the duration of services for the conventional therapy group was an average of 63% longer than for the robotic exoskeleton group, however each visit was 50% shorter in total time. Men had an 11% longer duration of services than women had. Participants with complete injuries had a duration of services that was approximately 1.72 times longer than participants with incomplete injuries. Perceived improvement was larger in the conventional group. CONCLUSIONS Locomotor/gait training strategies are distinctive for individuals with SCI using a robotic exoskeleton in a community wellness facility as episodes are shorter but individual sessions are longer. Participants' preferences and the ability to pay for ongoing services may be critical factors associated with the duration of outpatient services.
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Affiliation(s)
| | - Daniel Pinto
- College of Health Sciences, Marquette University, Milwaukee, Wisconsin.
| | - Chaithanya K Mummidisetty
- Max Näder Center for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois
| | - Arun Jayaraman
- Max Näder Center for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois; Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Candy Tefertiller
- Craig Hospital, Englewood, Colorado; University of Colorado, Denver, Colorado
| | - Susan Charlifue
- Craig Hospital, Englewood, Colorado; University of Colorado, Denver, Colorado
| | | | - Shuo-Hsiu Chang
- UT Health Science Center at Houston, Houston, Texas; Neurorecovery Research Center, TIRR Memorial Hermann, Houston, Texas
| | - Nicholas McCombs
- Max Näder Center for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois
| | | | - Edelle C Field-Fote
- Shepherd Center, Atlanta, Georgia; Division of Physical Therapy, Emory University School of Medicine, Atlanta, Georgia
| | - Allen W Heinemann
- Max Näder Center for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, Illinois; Physical Medicine and Rehabilitation, Northwestern University Feinberg School of Medicine, Chicago, Illinois
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Jackson SE, Brown J, Grabovac I, Cheeseman H, Osborne C, Shahab L. Smoking and Quitting Behavior by Sexual Orientation: A Cross-Sectional Survey of Adults in England. Nicotine Tob Res 2021; 23:124-134. [PMID: 32115647 PMCID: PMC7789956 DOI: 10.1093/ntr/ntaa042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 02/27/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVE To assess associations between sexual orientation and smoking and quitting behavior among adults in England. METHODS Data were collected from 112 537 adults (≥16 years) participating in a nationally representative monthly cross-sectional survey between July 2013 and February 2019. Sexual orientation was self-reported as heterosexual, bisexual, lesbian/gay, or prefer-not-to-say. Main outcomes were smoking status, e-cigarette use, cigarettes per day, time to first cigarette, motivation to stop smoking, motives for quitting, use of cessation support, and past-year quit attempts. Associations were analyzed separately for men and women using multivariable regression models adjusted for relevant covariates. RESULTS Smoking prevalence is now similar between gay (21.6%), prefer-not-to-say (20.5%) and heterosexual men (20.0%), and lesbian (18.3%) and heterosexual women (16.9%), but remains higher among bisexual men (28.2%, adjusted odds ratio [ORadj] = 1.41, 95% confidence interval [CI] = 1.11 to 1.79) and bisexual women (29.8%, ORadj = 1.64, 95% CI = 1.33 to 2.03) and lower among prefer-not-to-say women (14.5%, ORadj = 0.85, 95% CI = 0.72 to 0.99). Among smokers, bisexuals were less addicted than heterosexuals, with bisexual men smoking fewer cigarettes per day (Badj = -2.41, 95% CI = -4.06 to -0.75) and bisexual women less likely to start smoking within 30 min of waking (ORadj = 0.66, 95% CI = 0.45 to 0.95) than heterosexuals. However, motivation to stop smoking and quit attempts did not differ significantly. CONCLUSIONS In England, differences in smoking prevalence among people with different sexual orientations have narrowed, primarily driven by a larger decline in smoking rates among sexual minority groups than heterosexuals. Bisexual men and women remain more likely to smoke but have lower levels of addiction while being no less likely to try to quit. IMPLICATIONS This population-based study provides an up-to-date picture of smoking and quitting behavior in relation to sexual orientation among adults in England. Findings suggest that widely documented disparities in smoking prevalence have narrowed over recent years, with gay men and lesbian women no longer significantly more likely to smoke than heterosexuals, although smoking remains more common among bisexual men and women. Insights into differences in level of addiction, use of cessation support, and motives for quitting may help inform the development of targeted interventions to further reduce smoking among sexual minority groups.
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Affiliation(s)
- Sarah E Jackson
- Department of Behavioural Science and Health, University College London, London, UK
| | - Jamie Brown
- Department of Behavioural Science and Health, University College London, London, UK
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Igor Grabovac
- Department of Social and Preventive Medicine, Centre for Public Health, Medical University of Vienna, Vienna, Austria
| | | | | | - Lion Shahab
- Department of Behavioural Science and Health, University College London, London, UK
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Baig SA. Bayesian Inference: Understanding Experimental Data With Informative Hypotheses. Nicotine Tob Res 2020; 22:2118-2121. [PMID: 32610347 PMCID: PMC7593362 DOI: 10.1093/ntr/ntaa120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Accepted: 06/24/2020] [Indexed: 11/14/2023]
Affiliation(s)
- Sabeeh A Baig
- Center for Tobacco Products, Food and Drug Administration, Silver Spring, MD
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