DOCSLIB.ORG

Jhpiego Resource Package for Journal Manuscript Development: Support Materials

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Jhpiego Resource Package for Journal Manuscript Development: Support Materials Jhpiego Resource Package for Journal Manuscript Development Support Materials Tool 32: Types of Quantitative Study Designs Study designs can be divided into three types, as shown in the table below, based on whether they: 1. Randomly assign subjects to groups, and 2. Include a control group or multiple waves of measurement. The sections below describe and provide examples of experimental, quasi-experimental, and non- experimental study designs. QUASI- NON - STUDY DESIGN EXPERIMENTAL EXPERIMENTAL EXPERIMENTAL Random assignment of subjects to Yes No No group(s) Control group or multiple waves of Yes Yes No measurement Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials EXPERIMENTAL DESIGNS Experiments manipulate an independent variable and examine what the consequences are on another variable, the so-called dependent variable or outcome. In contrast, ‘‘natural experiments’’ assess the patterns between naturally occurring variables. Experimental designs vary in their rigor and ability to make causal inferences. The hallmark of experimental design is the random assignment of subjects to intervention and control groups. Example of an experimental study Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials QUASI-EXPERIMENTAL DESIGNS Like experimental designs, quasi-experimental study designs involve the manipulation of an independent variable to examine the consequence on another, dependent variable. Unlike experimental designs, however, subjects are not randomly assigned to groups. Example of a quasi-experimental study Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials NON-EXPERIMENTAL DESIGNS Non-experimental designs (which are also known as observational designs) do not involve random assignment of subjects to groups, nor is there a control or comparison group. Non-experimental designs also do not involve multiple waves of measurement. This type of design is very useful for descriptive research questions. Observational study designs are used when it is not feasible or not ethical to randomize groups to receive a certain exposure and determine whether it causes a particular outcome. For example, a classic example of an observational study design involves cigarette smoking: it would be unethical to designate certain people to begin smoking and then measure how many developed cancer. Observational studies may provide information to: Explain the causes of disease incidence and the determinants of disease progression, Predict the future health care needs of a population, and Control disease by studying ways to prevent disease and prolong life while living with disease. The main limitation of observational studies is that investigators do not have complete control over other variables related to the exposure and outcome, such as environmental factors or events that occur in the research area. As a result, observational study designs cannot be used to establish causality. The sub-sections below describe four non-experimental study designs that are often used in public health research: Descriptive cross-sectional studies, Cohort studies, Case-control studies, and Case-crossover studies. Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials Descriptive Cross-Sectional Studies Descriptive cross-sectional studies are a simple but common form of observational study design. For example, a researcher might survey patients about their opinions of health care services. Alternatively, a researcher might survey patients’ attitudes after providers have undergone specialized training (the intervention). This limitation of this post-test only design is that it lacks a comparison group and therefore the ability to conclude that the outcome was the result of the intervention. Example of a descriptive study Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials Cohort Studies This type of observational study follows a defined group------called the cohort------over time. The primary advantage of cohort studies is their ability to establish a temporal association between a particular exposure and a particular outcome. The choice of cohort depends on the hypothesis being tested, along with feasibility issues, such as the availability of records and ease of follow-up. Cohort studies are most feasible when the exposure and outcome of interest are relatively common. However, special cohorts have been used to study the health effects of rare exposures such as uncommon workplace chemicals, unusual diets, and uncommon lifestyles. Groups may be formed prospectively or retrospectively. In a prospective cohort study, participants are grouped on predetermined criteria (for example, smokers) and then followed into the future to observe outcomes of interest (for example, cancer). When the study commences, the outcomes have not yet developed and the investigator must wait for them to occur. In contrast, when a retrospective cohort study begins, both the exposures and outcomes have already occurred. The decision to conduct a retrospective or prospective study depends on the research question, practical constraints such as time and money, and the availability of suitable study populations and records. Cohorts may be closed or open. Members of a closed (or fixed) cohort are all enrolled at the same time and followed until a predetermined endpoint, such as death or diagnosis with a particular disease. In an open cohort, members may enter the study at different times. Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials Example of a cohort study Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials Case-Control Studies This type of observational study compares subjects who have a disease (called cases) with those who do not have that disease (called controls). The first step in case-control studies is formulating a disease or case definition based on a combination of signs and symptoms, physical and pathological examinations, and results of diagnostic tests. Cases are typically identified from hospital or clinic patient rosters, death certificates, special surveys, and reporting systems such as cancer or birth defects registries. Investigators consider both accuracy and efficiency when selecting a source for case identification, with the goal of identifying as many true cases of disease as quickly and cheaply as possible. Researchers who study the causes of disease prefer to select incident cases of disease, because they are interested in the factors that lead to the development of a disease rather than factors that affect its duration. However, epidemiologists sometimes have no choice but to rely on prevalent cases, for example, when studying an insidious disease whose exact onset is difficult to pinpoint. Studies using prevalent cases must be interpreted cautiously, because it is impossible to determine if the exposure is related to the inception of the disease, its duration, or a combination of the two. Controls come from the same population that produced the cases and may be matched with cases on particular characteristics. Investigators use several sources to identify controls. Investigators may sample: Individuals from the general population, Individuals attending a hospital or clinic, Friends or relatives identified by the cases, or Individuals who have died. Population controls are typically selected when cases are identified from a well-defined population, such as residents of a geographic area. After cases and controls are identified, their exposure histories are obtained and compared. If cases are found to have higher exposure than controls, after controlling for other important factors, the study’s hypothesis may merit testing through a more rigorous design, such as a cohort study or randomized controlled trial. Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials Example of a case-control study Copyright 2014 by Jhpiego Do Not Copy Jhpiego Resource Package for Journal Manuscript Development Support Materials Case-Crossover Study This type of observational study is a variant of the case-control study. Case-crossover studies were developed for settings in which the risk of the outcome is increased for only a brief time following the exposure. The period of increased risk following the exposure is termed the hazard period. In the case-crossover study, cases serve as their own controls, and the exposure frequency during the hazard period is compared to that from a control period. Because cases serve as their own controls, this design has several advantages. It eliminates confounding by characteristics such as gender and race and the bias that results from selecting unrepresentative controls. In addition, because variability is reduced, this design requires fewer subjects than a traditional case-control study. Example of a case-crossover study Recommended reading: Aschengrau, Serge 2008 Copyright 2014 by Jhpiego Do Not Copy.
Load more

Recommended publications
  • A Case-Crossover Study of Sleep and Childhood Injury
    A Case-Crossover Study of Sleep and Childhood Injury Francesca Valent, MD*; Silvio Brusaferro, MD*; and Fabio Barbone, MD, DrPH*‡ ABSTRACT. Objective. To evaluate the association n Italy (ϳ56 million inhabitants; 9 million chil- between sleep and wakefulness duration and childhood dren Ͻ15 years of age), ϳ500 children Ͻ15 years unintentional injury. of age are killed each year in unintentional inju- Study Design. Case-crossover study. I 1 ries. Homicides and suicides are much less frequent, Methods. Two hundred ninety-two injured children accounting for Ͻ10% of all fatal injuries among chil- who presented at the Children’s Emergency Center of dren.1 In Northern Italy, in 1995, injury mortality Udine, Italy, or their parents were interviewed after a rates (International Classification of Diseases, Ninth Re- structured questionnaire. Information was collected con- vision codes from 800 to 999) were 10 deaths/100 000 cerning sociodemographic variables, participant’s habits, and injury characteristics, including a brief description inhabitants under 1 year of age, 5/100 000 from 1 to of the accident dynamics. Sleep or wakefulness status of 4 years of age, and 6/100 000 from 5 to 14 years of the child was assessed retrospectively for each of the 48 age. Among infants, injury represented only 2% of hours before injury. For each child, we compared the 24 overall mortality, whereas in the 2 older age groups hours immediately before the injury (hours 1–24; case injuries accounted for 18% and 33% of all deaths, period) with hours 25 to 48 (control period). Nonparamet- respectively.2 Mortality, however, is just the tip of a ric tests were conducted to compare the difference of pyramid, where for each injury resulting in a death sleep duration between case and control periods.
    [Show full text]
  • A Phase I, Double Blind, Three-Way Crossover Study to Assess The
    A Phase I, Double Blind, Three-Way Crossover Study to Assess the Pharmacokinetic Profile of Cannabis Based Medicine Extract (CBME) Administered Sublingually in Variant Cannabinoid Ratios in Normal Healthy Male Volunteers (GWPK0215) G. W. Guy P. J. Robson SUMMARY. Primary objectives of this study were to assess the pharm- acokinetic characteristics of CBME when administered sublingually in different ratios, to determine if the pharmacokinetic profiles of THC and its metabolite 11-hydroxy-THC are different when administered sub- lingually in different formulations, and to characterise the pharmaco- kinetic profile of CBD when administered with THC in equal amounts. G. W. Guy and P. J. Robson are affiliated with GW Pharmaceuticals plc, Porton Down Science Park, Salisbury, Wiltshire, SP4 0JQ, UK. [Haworth co-indexing entry note]: “A Phase I, Double Blind, Three-Way Crossover Study to Assess the Pharmacokinetic Profile of Cannabis Based Medicine Extract (CBME) Administered Sublingually in Variant Cannabinoid Ratios in Normal Healthy Male Volunteers (GWPK0215).” Guy, G. W., and P. J. Robson. Co-published simultaneously in Journal of Cannabis Therapeutics (The Haworth Integrative Healing Press, an imprint of The Haworth Press, Inc.) Vol. 3, No. 4, 2003, pp. 121-152; and: Cannabis: From Pariah to Pre- scription (ed: Ethan Russo) The Haworth Integrative Healing Press, an imprint of The Haworth Press, Inc., 2003, pp. 121-152. Single or multiple copies of this article are available for a fee from The Haworth Document Delivery Service [1-800-HAWORTH, 9:00 a.m. - 5:00 p.m. (EST). E-mail address: docdelivery@ haworthpress.com]. http://www.haworthpress.com/store/product.asp?sku=J175 2003 by The Haworth Press, Inc.
    [Show full text]
  • Randomized, Double-Blind, Placebo-Controlled, Crossover Study of the Efficacy and Safety of Lisdexamfetamine Dimesylate in Adult
    UC Irvine UC Irvine Previously Published Works Title Randomized, double-blind, placebo-controlled, crossover study of the efficacy and safety of lisdexamfetamine dimesylate in adults with attention-deficit/hyperactivity disorder: novel findings using a simulated adult workplace environment design Permalink https://escholarship.org/uc/item/4kq3z3hd Journal Behavioral and Brain Functions, 6(1) ISSN 1744-9081 Authors Wigal, Timothy Brams, Matthew Gasior, Maria et al. Publication Date 2010-06-24 DOI http://dx.doi.org/10.1186/1744-9081-6-34 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Wigal et al. Behavioral and Brain Functions 2010, 6:34 http://www.behavioralandbrainfunctions.com/content/6/1/34 RESEARCH Open Access Randomized,Research double-blind, placebo-controlled, crossover study of the efficacy and safety of lisdexamfetamine dimesylate in adults with attention-deficit/hyperactivity disorder: novel findings using a simulated adult workplace environment design Timothy Wigal*1, Matthew Brams2, Maria Gasior3, Joseph Gao4, Liza Squires3, John Giblin5 for 316 Study Group Abstract Background: Duration of efficacy and safety of lisdexamfetamine dimesylate (LDX) was assessed in adults (18-55 years) with attention-deficit/hyperactivity disorder (ADHD) using the simulated adult workplace environment. Methods: After open-label dose optimization (4-week) with LDX, 30-70 mg/d, subjects entered a 2-week randomized, double-blind, placebo-controlled crossover phase. Efficacy assessments included the Permanent Product Measure of Performance (PERMP) total score (attempted+correct) measured predose and from 2 to 14 hours postdose, averaged across postdose sessions (primary) and at each time point vs placebo (secondary), and ADHD Rating Scale IV (ADHD- RS-IV) with adult prompts at baseline and crossover visits.
    [Show full text]
  • A Cross-Over Study to Evaluate the Effect of Glucagon-Like Peptide 1 on Women with Polycystic Ovarian Syndrome
    Volume 1- Issue 6 : 2017 DOI: 10.26717/BJSTR.2017.01.000534 Yu Liu. Biomed J Sci & Tech Res ISSN: 2574-1241 Review Article Open Access A Cross-Over Study to Evaluate the Effect of Glucagon-Like Peptide 1 on Women with Polycystic Ovarian Syndrome Yu Liu*1, Suyan Tian*2, Ming-Wen An3 and Lu Wang4 1Sir Run Run Hospital, Nanjing Medical University, Nanjing, Jiangsu, China 2Department of Endocrinology, Second Hospital of Jilin University, Changchun, Jilin, China 3Department of Mathematics, Vassar College, Poughkeepsie, New York, NY, USA 4Division of Clinical Research, First Hospital of Jilin University, Jilin, China Received: November 08, 2017; Published: November 15, 2017 *Corresponding author: Yu Liu, Sir Run Hospital, Nanjing Medical University, 109 Longman Avenue, Nanjing, Jiangsu, China, 211166, Email: Suyan Tian, Division of Clinical Research, First Hospital of Jilin University, 71 Xiamen Street, Changchun, Jilin, China, Email: Abstract Background: Crossover design is very popular for a study of new and developmental drugs. However this design tends to be misused regardless of whether it is suitable for underlying research questions. Method: Given that in clinical practice 2x2 cross over is the most commonly used design, the Hills- Arbitrage approach is suggested to with multiple time points within each stratum. analyze data. Furthermore, we propose fitting a linear mixed model and then conducting a likelihood ratio test to yield a single p-value on data Finding: Applying these methods to a real data, we evaluate effect of glucagon-like peptide 1 (GLP-1) on women with polycystic ovarian PCOS women is nevertheless clinically meaningful. Not only does it show a longer washout period is desired, but also it suggests GLP-1 may havesyndrome the same (PCOS).
    [Show full text]
  • Inferences on Treatment and Carryover Effects in Two-Period Two-Sequence Crossover Designs
    Research Article Curr Trends Biomedical Eng & Biosci Volume 11 Issue 5 - February 2018 Copyright © All rights are reserved by Sam Weerahandi DOI: 10.19080/CTBEB.2018.11.555821 Inferences on Treatment and Carryover Effects in Two-Period Two-Sequence Crossover Designs Vladimir Geneus1, Chunming Li1, Sam Weerahandi1*, Ed Whalen1 and Ching Ray Yu2 1Department of Statistics, Florida State University, USA 2Department of Statistics, Pfizer Inc., USA Submission: January 13, 2018; Published: February 01, 2018 *Corresponding author: Sam Weerahandi, Department of Statistics, Florida State University, 23 Chestnut St, Edison, NJ 08817, USA, Email: Abstract It is well known that, in the absence of 4 sequences or a long washout period, it is not possible for classical methods to separate out the treatment effects and carryover effects of a crossover design involving two treatments. Motivated by self-contradictory, visually clear results from a standard mixed effects model repeated measures (MMRM) type analysis of a 2X2 crossover, we develop a method to take advantage of repeated measures in each period to make inferences on treatments and carryover effects. The proposed model applied to our data rectified the anomaly in our application. Results from a simulation study are also included to demonstrate the advantage of the proposed approach over the regular MMRM approach. Introduction and Background method failing to sort things out, in this article we propose how can see from the figure, and having seen the widely used MMRM one can separate out the treatment effects and carryover effects by taking advantage the repeated measures. In fact, the proposed method can be applied even if there is no washout period.
    [Show full text]
  • A Systematic Review of Quasi-Experimental Study Designs in the Fields of Infection Control and Antibiotic Resistance
    INVITED ARTICLE ANTIMICROBIAL RESISTANCE George M. Eliopoulos, Section Editor A Systematic Review of Quasi-Experimental Study Designs in the Fields of Infection Control and Antibiotic Resistance Anthony D. Harris,1,2 Ebbing Lautenbach,3,4 and Eli Perencevich1,2 1 2 Division of Health Care Outcomes Research, Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, and Veterans Downloaded from https://academic.oup.com/cid/article/41/1/77/325424 by guest on 24 September 2021 Affairs Maryland Health Care System, Baltimore, Maryland; and 3Division of Infectious Diseases, Department of Medicine, and 4Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania We performed a systematic review of articles published during a 2-year period in 4 journals in the field of infectious diseases to determine the extent to which the quasi-experimental study design is used to evaluate infection control and antibiotic resistance. We evaluated studies on the basis of the following criteria: type of quasi-experimental study design used, justification of the use of the design, use of correct nomenclature to describe the design, and recognition of potential limitations of the design. A total of 73 articles featured a quasi-experimental study design. Twelve (16%) were associated with a quasi-exper- imental design involving a control group. Three (4%) provided justification for the use of the quasi-experimental study design. Sixteen (22%) used correct nomenclature to describe the study. Seventeen (23%) mentioned at least 1 of the potential limitations of the use of a quasi-experimental study design.
    [Show full text]
  • Estimate Carryover Effect in Clinical Trial Crossover Designs
    Paper PO16 Estimate Carryover Effect in Clinical Trial Crossover Designs David Shen, WCI, Inc. Zaizai Lu, AstraZeneca Pharmaceuticals ABSTRACT The crossover design to study the differences in treatments yields a more efficient comparison of treatments than a parallel design. Subjects are on their own controls. The within-patient variation is less than between-patient variation. Crossover design requires a smaller sample size than a parallel design, but achieves same level of statistical power and precision. However, there might be a potential carryover effect in crossover design. The paper discusses how carryover effect may bias statistical results, and provides a method to test carryover effects. SAS procedures such as TTEST, GLM and MIXED are also included. INTRODUCTION A crossover trial is one in which individual subjects are given a sequence of treatments rather that one treatment at any time. The subjects cross over from one treatment to another treatment during the course of the trial. This is in contrast to a parallel design where subjects are randomized to a treatment and remain on that treatment throughout the whole trial. Crossover design is commonly used in the early phase trials such as: • Pharmacokinetic studies to establish concentration time profiles • Bioequivalence • Food interaction studies • Dose proportionality • Dose escalation studies for investigating maximum tolerated does (MTD) In clinical trials, the disease should be chronic and stable. Quickly reversible treatments are more suitable such as for asthma, arthritis, gastro-esophageal reflux and hypertension. The treatments should not be a complete cure but only alleviate the disease condition. If one treatment cures the patient disease in the first period, then the other treatment will have no chance to demonstrate its effectiveness in the second period.
    [Show full text]
  • STATISTICAL ANALYSES PLAN a Replicated Crossover Study to Explore Individual Variability of Appetite Responses to a Standardised
    STATISTICAL ANALYSES PLAN A replicated crossover study to explore individual variability of appetite responses to a standardised meal and any moderating influence of the FTO gene Version 1 Investigators Professor David Stensel Professor Greg Atkinson Ms Fernanda Reistenbach Goltz Address School of Sport, Exercise and Health Sciences Loughborough University Leicestershire LE11 3TU United Kingdom Correspondence Professor David Stensel: +44(0)1509 226344, [email protected] Statistical analyses plan Unique protocol ID: R17-P178 Date: 03-12-2018 Statistical analyses plan Between-genotype differences in participant characteristics will be quantified using linear mixed models with group (AA versus TT) modelled as a fixed factor. The presence of interindividual differences in blood marker and perceived appetite responses to a standardised meal will be examined according to three analytical approaches (Atkinson and Batterham, 2015; Senn et al., 2011; Senn, 2016). The three approaches, detailed recently by Goltz et al. (2018), will be as follows: (i) The association between the first and second replicate of control-adjusted treatment effect will be quantified for each outcome using Pearson’s correlation coefficients (Senn, 2016). The first meal condition in any participant’s sequence will be paired to the first control condition in the same individual’s sequence. Thresholds of 0.1, 0.3 and 0.5 will be used to label correlation coefficients as small, moderate and large, respectively (Cohen, 1988). This correlation coefficient quantifies the consistency of meal effect across the replicated experimental conditions. (ii) The following equation (Atkinson and Batterham, 2015) will be used to provide an overall estimate of the true (control condition adjusted) between-subject differences in treatment response: SD = SD SD 2 2 IR � M − C SDIR represents the true interindividual variation in treatment effect.
    [Show full text]
  • Exact Calculation of Power and Sample Size in Bioequivalence Studies Using Two One-Sided TestsŽ Meiyu Shen,A* Estelle Russek-Cohen,B and Eric V
    MAIN PAPER (wileyonlinelibrary.com) DOI: 10.1002/pst.1666 Published online 5 December 2014 in Wiley Online Library Exact calculation of power and sample size in bioequivalence studies using two one-sided tests Meiyu Shen,a* Estelle Russek-Cohen,b and Eric V. Sludc,d The number of subjects in a pharmacokinetic two-period two-treatment crossover bioequivalence study is typically small, most often less than 60. The most common approach to testing for bioequivalence is the two one-sided tests procedure. No explicit mathematical formula for the power function in the context of the two one-sided tests procedure exists in the statistical literature, although the exact power based on Owen’s special case of bivariate noncentral t-distribution has been tabulated and graphed. Several approximations have previously been published for the probability of rejection in the two one-sided tests procedure for crossover bioequivalence studies. These approximations and associated sample size formulas are reviewed in this article and compared for various parameter combinations with exact power formulas derived here, which are computed analytically as univariate integrals and which have been validated by Monte Carlo simulations. The exact formulas for power and sample size are shown to improve markedly in realistic parameter settings over the previous approximations. Copyright © 2014 John Wiley&Sons,Ltd. Keywords: bioequivalence; single endpoint; sample size; power; crossover; pharmacokinetic study 1. INTRODUCTION The null hypothesis, H0,statesthatT and R are not equivalent. The alternative hypothesis representing equivalence, In a typical pharmacokinetic two-period two-treatment crossover Ha, is the intersection of the two one-sided parameter regions, bioequivalence study, subjects are randomized to one group f1 <T Rg and fT R <2g.
    [Show full text]
  • Statistical Review(S)
    CENTER FOR DRUG EVALUATION AND RESEARCH APPLICATION NUMBER: 21-977 STATISTICAL REVIEW(S) DEPARTMENT OF HEALTH AND HUMAN SERVICES PUBLIC HEALTH SERVICE FOOD AND DRUG ADMINISTRATION CENTER FOR DRUG EVALUATION AND RESEARCH STATISTICAL REVIEW AND EVALUATION Clinical Studies NDA/Serial Number: 21-977 (N000) Drug Name: Lisdexamfetamine Caps Indication: ADHD in Pediatric Population (Ages 6-12) Applicant: New River Pharmaceuticals, Inc Dates: Date of Document: 12/06/2005 PDUFA Due Date: 10/06/2006 Review Priority: Standard Biometrics Division: Biometrics I, HFD-710 Statistical Reviewer: Yeh-Fong Chen, Ph.D. Concurring Reviewers: Peiling Yang, Ph.D. Kooros Mahjoob, Ph.D. Medical Division: Division of Psychiatry Drug Products, HFD-130 Clinical Team: Clinical Reviewer: Michelle Chuen, M.D. Clinical Team Leader: Ni Aye Khin, M.D. Project Manager: Susan Player 1 Table of Contents 1. EXECUTIVE SUMMARY ...................................................................................................................... 3 1.1 CONCLUSIONS AND RECOMMENDATIONS............................................................................... 3 1.2 BRIEF OVERVIEW OF CLINICAL STUDIES.................................................................................. 3 1.3 STATISTICAL ISSUES AND FINDINGS .......................................................................................... 3 2. INTRODUCTION .................................................................................................................................... 4 2.1 OVERVIEW........................................................................................................................................
    [Show full text]
  • Selection Bias and Confounding in Case-Crossover Analyses of Environmental Time-Series Data Thomas F
    Selection Bias and Confounding in Case-Crossover Analyses of Environmental Time-Series Data Thomas F. Bateson1 and Joel Schwartz2 The case-crossover study design is a popular analytic tool for hazard periods, even when the distribution of exposure is estimating the effects of triggers of acute outcomes by envi- stationary. This bias can be estimated and removed. Selection ronmental exposures. Although this approach controls for bias also occurs when the distribution of exposure is nonsta- time-invariant confounders by design, it may allow for selec- tionary, but the adjusted symmetric bidirectional case-cross- tion bias and confounding by time-varying factors. We con- over methodology substantially controls for this. Confounding ducted a simulation study of the sensitivity of the symmetric results from a common temporal pattern in the exposure and bidirectional case-crossover design to time-varying patterns in the outcome time series, but can also be the result of patterns exposure and outcome. We identified the effects of selection in exposure and outcome that, although asymptotically uncor- bias and confounding on symmetric bidirectional case-cross- related, are correlated at finite series lengths. All three biases over results and offer strategies to eliminate or reduce these are reduced by choosing shorter referent-spacing lengths. This biases. Selection bias results when exposure in the reference effect is illustrated using data on air pollution and daily deaths periods is not identically representative of exposure in the in Chicago. (EPIDEMIOLOGY 2001;12:654–661) Keywords: epidemiologic research designs, epidemiologic methods, case-crossover studies, case-referent studies, environmental epidemiology, epidemiologic biases, selection bias, confounding variables The case-crossover design of Maclure1 represents an rectional (SBI) referent sampling with close referents attractive approach to examining the impact of time- reduced that bias.
    [Show full text]
  • Statistical Review and Evaluation
    U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research Office of Translational Sciences Office of Biostatistics S TATISTICAL R EVIEW AND E VA L U AT I O N CLINICAL STUDIES NDA/Serial Number: 22-210 / 000 Drug Name: Zentase Pancreatic Enzyme Product Delayed-Release Capsules (EUR-1008) Indication(s): Exocrine Pancreatic Insufficiency (EPI) Applicant: Eurand Pharmaceuticals Limited (EPL) Date(s): Letter Date: 12/14/2007 Stamp Date: 12/17/2007 Date Forwarded to DDR: 12/19/2007 Date Received by Reviewer: 4/21/2008 PDUFA Date: 6/17/2008 Review Priority: Priority Biometrics Division: Division of Biometrics 3 Statistical Reviewer: Freda W. Cooner, Ph.D. Concurring Reviewers: Mike Welch, Ph.D. Medical Division: Division of Gastroenterology Products Clinical Team: Marjorie F. Dannis, M.D., Medical Reviewer Anne Pariser, M.D., Team Leader Project Manager: Maureen Dewey Keywords: Clinical studies, NDA review, Crossover design, Repeated measure ANOVA, Subgroup analyses Table of Contents 1. EXECUTIVE SUMMARY ..................................................................................................................................3 1.1 CONCLUSIONS AND RECOMMENDATIONS .......................................................................................................3 1.2 BRIEF OVERVIEW OF CLINICAL STUDIES ........................................................................................................3 1.3 STATISTICAL ISSUES AND FINDINGS ...............................................................................................................4
    [Show full text]