Download or read book Causal Inference and the Comparative Interrupted Time Series Design written by Travis St. Clair and published by . This book was released on 2014 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers are increasingly using comparative interrupted time series (CITS) designs to estimate the effects of programs and policies when randomized controlled trials are not feasible. In a simple interrupted time series design, researchers compare the pre-treatment values of a treatment group time series to post-treatment values in order to assess the impact of a treatment, without any comparison group to account for confounding factors. The CITS design is a version of the ITS design in which both a treatment and a comparison group are evaluated both before and after the onset of a treatment. A growing body of literature is employing a within study comparison (WSC) methodology to examine the validity of the CITS model. WSC studies empirically estimate the extent to which a given observational study reproduces the results of a randomized controlled trial (RCT) when both share the same treatment group, and represent a rigorous method of evaluating non-experimental designs using real data. A number of recent within-study comparisons have demonstrated that CITS can produce estimates that are comparable to those from a randomized controlled trial (RCT) in practice. In the St. Clair et al. (2014) application, the authors found that correspondence with the RCT was possible when the CITS model accounted for baseline trends, but that additional time points could actually increase bias when the pre-treatment trend was not modeled correctly. Examination of the pretreatment trends in this data set showed clearly that in at least one of the outcomes the treatment and comparison groups had different slopes in the pretreatment period, and as a result the "parallel trends" assumption often invoked in the difference-in-difference literature was clearly violated. This paper employs a within study comparison (WSC) methodology to examine the performance of two approaches: (1) a more flexible modeling approach, which employs year fixed-effects rather than trying to parametrically model the pretest trend; and (2) match treatment and comparison cases to reduce reliance on modeling the pretreatment trend. The paper then compares the approaches to the performance of the baseline mean and baseline slope models across three datasets. The purpose of this research is two-fold: (1) to examine what approach, if any, works in the unclear functional form case; and (2) to examine the relative superiority of the different approaches across the three datasets in terms of both bias reduction and precision. Tables and figures are appended.

Download or read book Experimental and Quasi experimental Designs for Generalized Causal Inference written by William R. Shadish and published by Cengage Learning. This book was released on 2002 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.

Download or read book Interrupted Time Series Analysis written by David McDowall and published by Oxford University Press, USA. This book was released on 2019 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It provides example analyses of social, behavioral, and biomedical time series to illustrate a general strategy for building AutoRegressive Integrated Moving Average (ARIMA) impact models. Additionally, the book supplements the classic Box-Jenkins-Tiao model-building strategy with recent auxiliary tests for transformation, differencing, and model selection. Not only does the text discuss new developments, including the prospects for widespread adoption of Bayesian hypothesis testing and synthetic control group designs, but it makes optimal use of graphical illustrations in its examples. With forty completed example analyses that demonstrate the implications of model properties, Interrupted Time Series Analysis will be a key inter-disciplinary text in classrooms, workshops, and short-courses for researchers familiar with time series data or cross-sectional regression analysis but limited background in the structure of time series processes and experiments.

Download or read book Design and Analysis of Time Series Experiments written by Richard McCleary and published by Oxford University Press. This book was released on 2017 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Time Series Experiments develops methods and models for analysis and interpretation of time series experiments while also addressing recent developments in causal modeling. Unlike other time series texts, it integrates the statistical issues of design, estimation, and interpretation with foundational validity issues. Drawing on examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, this text addresses researchers and graduate students in a wide range of the behavioral, biomedical, and social sciences.

Download or read book Design and Analysis of Time Series Experiments written by Richard McCleary and published by Oxford University Press. This book was released on 2017-05-11 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Time Series Experiments presents the elements of statistical time series analysis while also addressing recent developments in research design and causal modeling. A distinguishing feature of the book is its integration of design and analysis of time series experiments. Readers learn not only how-to skills but also the underlying rationales for design features and analytical methods. ARIMA algebra, Box-Jenkins-Tiao models and model-building strategies, forecasting, and Box-Tiao impact models are developed in separate chapters. The presentation of the models and model-building assumes only exposure to an introductory statistics course, with more difficult mathematical material relegated to appendices. Separate chapters cover threats to statistical conclusion validity, internal validity, construct validity, and external validity with an emphasis on how these threats arise in time series experiments. Design structures for controlling the threats are presented and illustrated through examples. The chapters on statistical conclusion validity and internal validity introduce Bayesian methods, counterfactual causality, and synthetic control group designs. Building on the earlier time series books by McCleary and McDowall, Design and Analysis of Time Series Experiments includes recent developments in modeling, and considers design issues in greater detail than does any existing work. Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, the text is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. It will appeal to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference.

Download or read book Turning Around Low Performing Schools in Chicago written by Marisa De la Torre and published by . This book was released on 2012-02-05 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report finds that four years after undergoing dramatic reform efforts such as turnaround, very low-performing elementary schools in Chicago closed the gap in test scores with the system average by almost half in reading and two-thirds in math. The improvements took time to develop; test scores were not significantly better in the first year of reform, but grew larger over time. The study examined five different reform models initiated by the Chicago Public Schools (CPS) in 36 elementary and high schools identified as chronically low performing. The five reform models were: Reconstitution; School Closure and Restart; School Turnaround Specialist Program; Academy for Urban School Leadership; and Office of School Improvement. Each is consistent with one of the four improvement models recommended by the federal government (turnaround, transformation, restart, and school closure). Despite the attention and activity surrounding the models, there is a lack of research on whether or how they work. To begin to address this knowledge gap, CCSR and AIR partnered to examine dramatic interventions in Chicago, an early adopter of such reforms. The report also finds high schools that underwent reform did not show significant improvements in absences or ninth grade on-track-to-graduate rates over matched comparison schools, however recent high school efforts look more promising than earlier ones. Changes in student populations varied across reform models. Schools that underwent these reforms and remained neighborhood schools generally served the same students, and the same types of students, as before intervention. Schools that were closed and replaced with charter or contract schools generally served more advantaged students after intervention. The teacher workforce after intervention across all models was more likely to be white, younger, and less experienced.

Download or read book Commercial Motor Vehicle Driver Fatigue Long Term Health and Highway Safety written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2016-09-12 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.

Download or read book Interrupted Time Series Analysis written by David McDowall and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays in Causal Inference written by Raiden B. Hasegawa and published by . This book was released on 2019 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: In observational studies, identifying assumptions may fail, often quietly and without notice, leading to biased causal estimates. Although less of a concern in randomized trials where treatment is assigned at random, bias may still enter the equation through other means. This dissertation has three parts, each developing new methods to address a particular pattern or source of bias in the setting being studied. In the first part, we extend the conventional sensitivity analysis methods for observational studies to better address patterns of heterogeneous confounding in matched-pair designs. We illustrate our method with two sibling studies on the impact of schooling on earnings, where the presence of unmeasured, heterogeneous ability bias is of material concern. The second part develops a modified difference-in-difference design for comparative interrupted time series studies. The method permits partial identification of causal effects when the parallel trends assumption is violated by an interaction between group and history. The method is applied to a study of the repeal of Missouri's permit-to-purchase handgun law and its effect on firearm homicide rates. In the final part, we present a study design to identify vaccine efficacy in randomized control trials when there is no gold standard case definition. Our approach augments a two-arm randomized trial with natural variation of a genetic trait to produce a factorial experiment. The method is motivated by the inexact case definition of clinical malaria.

Download or read book Quasi experimentation written by Thomas D. Cook and published by . This book was released on 1979 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents some quasi-experimental designs and design features that can be used in many social research settings. The designs serve to probe causal hypotheses about a wide variety of substantive issues in both basic and applied research. Each design is assessed in terms of four types of validity, with special stress on internal validity. Although general conclusions are drawn about the strengths and limitations of each design, emphasis is also placed on the fact that the relevant threats to valid inference are specific to each research setting. Consequently, a threat that is usually associated with a particular design need not invariably be associated with that design.

Download or read book Improving Health Research on Small Populations written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-08-02 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing diversity of population of the United States presents many challenges to conducting health research that is representative and informative. Dispersion and accessibility issues can increase logistical costs; populations for which it is difficult to obtain adequate sample size are also likely to be expensive to study. Hence, even if it is technically feasible to study a small population, it may not be easy to obtain the funding to do so. In order to address the issues associated with improving health research of small populations, the National Academies of Sciences, Engineering, and Medicine convened a workshop in January 2018. Participants considered ways of addressing the challenges of conducting epidemiological studies or intervention research with small population groups, including alternative study designs, innovative methodologies for data collection, and innovative statistical techniques for analysis.

Download or read book Quasi Experimentation written by Charles S. Reichardt and published by Guilford Publications. This book was released on 2019-09-02 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.

Download or read book Case Studies and Causal Inference written by I. Rohlfing and published by Springer. This book was released on 2012-09-26 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: A discussion of the case study method which develops an integrative framework for causal inference in small-n research. This framework is applied to research design tasks such as case selection and process tracing. The book presents the basics, state-of-the-art and arguments for improving the case study method and empirical small-n research.

Download or read book Multiple Time Series Models written by Patrick T. Brandt and published by SAGE. This book was released on 2007 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.

Download or read book Interrupted Time Series Analysis written by David McDowall and published by SAGE Publications, Incorporated. This book was released on 1980-08 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes ARIMA or Box Tiao models, widely used in the analysis of interupted time series quasi-experiments, assuming no statistical background beyond simple correlation. The principles and concepts of ARIMA time series analyses are developed and applied where a discrete intervention has impacted a social system. '...this is the kind of exposition I wished I had had some ten years ago when venturing into the world of autoregressive, moving-average (ARIMA) models of time-series analysis...This monograph nicely lays out a method for assessing the impact of a discrete policy or event of some importance on behavior which can be continuously observed...If widely used, as I hope, it will save a generation of social scientists fro

Download or read book Developing a Protocol for Observational Comparative Effectiveness Research A User s Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Download or read book Experimental and Quasi Experimental Designs for Research written by Donald T. Campbell and published by Ravenio Books. This book was released on 2015-09-03 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.