Chapter 4 Research Methodology
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Evaluation Design Report for the National Cancer Institute's
February 2009 Evaluation Design Report for the National Cancer Institute’s Community Cancer Centers Program (NCCCP) Final Report Prepared for Steve Clauser, PhD Chief, Outcomes Research Branch Applied Research Program Division of Cancer Control and Population Sciences National Cancer Institute Executive Plaza North, Room 4086 6130 Executive Boulevard, (MSC 7344) Bethesda, MD 20892-7344 Prepared by Debra J. Holden, PhD Kelly J. Devers, PhD Lauren McCormack, PhD Kathleen Dalton, PhD Sonya Green, MPH Katherine Treiman, PhD RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709 RTI Project Number 0210903.000.005 RTI Project Number 0210903.0001.005 Evaluation Design Report for the National Cancer Institute’s Community Cancer Centers Program (NCCCP) Final Report February 2009 Prepared for Steve Clauser, PhD Chief, Outcomes Research Branch Applied Research Program Division of Cancer Control and Population Sciences National Cancer Institute Executive Plaza North, Room 4086 6130 Executive Boulevard, (MSC 7344) Bethesda, MD 20892-7344 Prepared by Debra J. Holden, PhD Kelly J. Devers, PhD Lauren McCormack, PhD Kathleen Dalton, PhD Sonya Green, MPH Katherine Treiman, PhD RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709 Contents Section Page Acronyms Error! Bookmark not defined. Executive Summary ES-Error! Bookmark not defined. 1. Introduction Error! Bookmark not defined. 1.1 Overview of the NCCCP Error! Bookmark not defined. 1.2 Summary of the NCCCP Sites Error! Bookmark not defined. 1.3 Process Completed for an Evaluability Assessment Error! Bookmark not defined. 1.3.1 Step 1: Pilot Site Evaluability Assessment (September 2007–June 2008) .................................................. Error! Bookmark not defined. 1.3.2 Step 2: Engage Stakeholders (September 2007–September 2008)Error! Bookmark not defined. -
Quantifying Anomia: Development of a Scale
ABSTRACT QUANTIFYING ANOMIA: DEVELOPMENT OF A SCALE Anomie refers to a weakening of cultural values and social norms. One interpretation is that anomie exists because of moral deregulation when normative rules begin deteriorating, while another suggests that it is a product of insufficient means to reach goals, forcing individuals to seek deviant modalities and paths (Agnew, 1980). While multiple scales have been developed in an attempt to measure the construct, the purpose of this study was to build upon and combine scales from 1956 to 2011 to produce an instrument that quantifies anomie/anomia using factor analyses. Four scales of anomia were compiled and administered to 416 Fresno State undergraduate students. The findings suggest that the final anomia scale has good internal consistency and correlates with materialism, happiness, and social desirability. However, no expected significant differences were found across gender, age, income, marital status, and race/ethnicity. Anthony Yang August 2015 QUANTIFYING ANOMIA: DEVELOPMENT OF A SCALE by Anthony Yang A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts in Psychology in the College of Science and Mathematics California State University, Fresno August 2015 APPROVED For the Department of Psychology: We, the undersigned, certify that the thesis of the following student meets the required standards of scholarship, format, and style of the university and the student's graduate degree program for the awarding of the master's degree. Anthony Yang Thesis Author Robert Levine (Chair) Psychology Constance Jones Psychology Deborah Helsel Sociology For the University Graduate Committee: Dean, Division of Graduate Studies AUTHORIZATION FOR REPRODUCTION OF MASTER’S THESIS X I grant permission for the reproduction of this thesis in part or in its entirety without further authorization from me, on the condition that the person or agency requesting reproduction absorbs the cost and provides proper acknowledgment of authorship. -
Methods Used in the Development of the Global Roads Open Access Data Set (Groads), Version 1
Methods Used in the Development of the Global Roads Open Access Data Set (gROADS), Version 1 Table of Contents Introduction ................................................................................................................................................................... 2 Data Assessment and Selection ..................................................................................................................................... 2 Root Mean Square Error (RMSE) ............................................................................................................................... 2 Validation against Google Earth (GE) imagery .......................................................................................................... 4 Calculating total length of roads ............................................................................................................................... 6 Choosing a data set for further edits ........................................................................................................................ 8 Data ingest: Creating and populating geodatabases ..................................................................................................... 8 Data editing ................................................................................................................................................................... 9 Creating a topology .................................................................................................................................................. -
Chronic Juvenile Offenders Final Results from the Skillman Aftercare Experiment
If you have issues viewing or accessing this file contact us at NCJRS.gov. ------------------------- --- -- -- - "- 'R'"-A KlO-'- ,.,-- .. ' - . ':'-' '.: . ,': :", ': ".' ".: R:I.. ~· .. ,.: ... :. ~ .... '.~, . ' ....'. " Chronic Juvenile Offenders Final Results from The Skillman Aftercare Experiment Peter W. Greenwood, Elizabeth Piper Deschenes, John Adams The research described in this report was supported by The Skillman Foundatiqn, Grant No. 91-296. Library of Congress Cataloging In Publication Data Greenwood, Peter W. Chronic juvenile offenders : fmal results from the Skillman aftercare experiment I Peter W. Greenwood, Elizabeth Piper Deschenes, John Adams. p. em. "Supported by The Skillman Foundation." "MR-220-SKF." Includes bibliographical references (p. ). ISBN 0-8330-1477-3 1. Juvenile delinquents-Rehabilitation-Michigan-Detroit. 2. Juvenile delinquents-Rehabilitation-Pennsylvania-Pittsburgh. 3. Social work with juvenile delinquents-Michigan -Detroit. 4. Social work with juvenile delinquents-Pennsylvania-Pittsburgh. I. Deschenes, Elizabeth Piper, 1953- ll. Adams, Jolm. 1956- HV9106.D5G74 1994 364.3'6'Q974886-dc20 9340155 CIP RAND is a nonprofit institution that seeks to improve public policy through research and analysis. RAND's publications do not necessarily reflect the opinions or policies of its research sponsors. Published 1993 by RAND 1700 Main Street, P.O. Box 2138, Santa Monica, CA 90407-2138 To obtain information about RAND studies or to order documents, call Distribution Services, (310) 451-7002 • Chronic Ju~{)enile Offeltders Final Results from The Skillman • Aftercare Experiment Peter W. Greenwood, Elizabeth Piper Deschenes, John Adams Supported by The Skillman Foundation •••• < ."'" •••• , ;- ." 151575 U.S. Department of Justice Nationallnstltule of Justice This document has been reproduced exactly as received from the person or organization originating it. Points of view or opinions stated in this document are those of the authors and do not necessarily represent the official position or policies of the National Institute 01 Justice. -
DHS Data Editing and Imputation Trevor Croft
DHS Data Editing and Imputation Trevor Croft, Demographic and Health Surveys Abstract Producing good quality demographic and health data and making it accessible to data users worldwide is one of the main aims of the Demographic and Health Surveys program. However, large scale surveys in developing countries, particularly those collecting retrospective data, are prone to poor reporting. Survey data have suffered traditionally from incomplete and inconsistent reporting, To handle these problems, DHS performed extensive data editing operations. In addition, imputation procedures were established to deal with partial reporting of dates of key events in the respondent's life. General techniques for handling incomplete and inconsistent data are considered. The paper then presents the DHS approach to data editing. The major focus is on the editing of dates of events and the intervals between events. The editing and imputation process starts with the calculation of initial logical ranges for each date, and gradually constrains these ranges to produce final logical ranges. Inconsistent data are reported in error listings during this process. Dates are imputed for events with incomplete reporting within these final logical ranges. The levels of imputation required in the DHS-I surveys are presented. Various problem areas involved with the imputation of incomplete dates are explained. These include biases caused by questionnaire design, miscalculation of dates by interviewers and ancillary data biases. Problems relating to fine temporal variables and to unconstrained ranges for dates are also reviewed. Finally, the changes introduced as part of the editing and imputation procedures for DHS- II to resolve some of the problem areas are presented and ideas for further improvements are discussed. -
Data Management, Analysis Tools, and Analysis Mechanics
Chapter 2 Data Management, Analysis Tools, and Analysis Mechanics This chapter explores different tools and techniques for handling data for research purposes. This chapter assumes that a research problem statement has been formulated, research hypotheses have been stated, data collection planning has been conducted, and data have been collected from various sources (see Volume I for information and details on these phases of research). This chapter discusses how to combine and manage data streams, and how to use data management tools to produce analytical results that are error free and reproducible, once useful data have been obtained to accomplish the overall research goals and objectives. Purpose of Data Management Proper data handling and management is crucial to the success and reproducibility of a statistical analysis. Selection of the appropriate tools and efficient use of these tools can save the researcher numerous hours, and allow other researchers to leverage the products of their work. In addition, as the size of databases in transportation continue to grow, it is becoming increasingly important to invest resources into the management of these data. There are a number of ancillary steps that need to be performed both before and after statistical analysis of data. For example, a database composed of different data streams needs to be matched and integrated into a single database for analysis. In addition, in some cases data must be transformed into the preferred electronic format for a variety of statistical packages. Sometimes, data obtained from “the field” must be cleaned and debugged for input and measurement errors, and reformatted. The following sections discuss considerations for developing an overall data collection, handling, and management plan, and tools necessary for successful implementation of that plan. -
Investigate the Relationship Between Socio-Economic Class and Tendency to Delinquency Among Students of Rey City in Tehran
INTERNATIONAL JOURNAL OF ENVIRONMENTAL & SCIENCE EDUCATION 2017, VOL. 12, NO. 4, 851-864 OPEN ACCESS Investigate the relationship between socio-economic class and tendency to delinquency among students of Rey city in Tehran Dr. Abdolreza Bagheri Bonjar Faculty member of Shahed University ABSTRACT Delinquency is a social phenomenon and has social context though biological factors, psychological, geographical, ethnic, racial and other items in the forming and occurring type of delinquency play an important role, explain the issue is on the basis of the social environment, limiting attitude of sociology scope in particular, the performance of the smallest and the most important social institution ie family that plays an important role in cooperation and homogeneous of normative behaviors of individuals with social environment. This study is conducted aimed to investigate the relationship between socio-economic class and delinquency rate with survey method. The sample population consisted of 260 students of Rey that its data is collected using a questionnaire. In this study to show the relationship between socioeconomic class and delinquency, several views is used such as Merton, Weber, and.., research findings indicate that there is a significant relationship between social class and delinquency meanwhile variables of social class (job and income and education) have had inverse relationship with delinquency, the more the rate of job and income and education of individual is high, the delinquency rate decreases. KEYWORDS ARTICLE HISTORY socio-economic class, tendency to delinquency, students Received 10 March 2017 Revised 18 April 2017 Accepted 12 May 2017 Introduction Delinquency of children and adolescents is the complex social issues and problems of today's world. -
An Introduction to the Data Editing Process
1 AN INTRODUCTION TO THE DATA EDITING PROCESS by Dania P. Ferguson United States Department of Agriculture National Agricultural Statistics Service Abstract: A primer on the various data editing methodologies, the impact of their usage, available supporting software, and considerations when developing new software. I. INTRODUCTION The intention of this paper is to promote a better understanding of the various data editing methods and the impact of their usage as well as the software available to support the use of the various methodologies. It is hoped that this paper will serve as: - a brief overview of the most commonly used editing methodologies, - an aid to organize further reading about data editing systems, - a general description of the data editing process for use by designers and developers of generalized data editing systems. II. REVIEW OF THE PROCESS Data editing is defined as the process involving the review and adjustment of collected survey data. The purpose is to control the quality of the collected data. This process is divided into four (4) major sub-process areas. These areas are: - Survey Management - Data Capture - Data Review - Data Adjustment The rest of this section will describe each of the four (4) sub-processes. 1. Survey Management The survey management functions are: a) completeness checking, and b) quality control including audit trails and the gathering of cost data. These functions are administrative in nature. Completeness checking occurs at both survey and questionnaire levels. 2 At survey level, completeness checking ensures that all survey data have been collected. It is vitally important to account for all samples because sample counts are used in the data expansion procedures that take place during Summary. -
Social Network Analysis As a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel † Behavioral Intention to Revisit and Recommend
sustainability Article Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel y Behavioral Intention to Revisit and Recommend Deukhee Park 1, Gyehee Lee 2,* , Woo Gon Kim 1 and Taegoo Terry Kim 3 1 International Center for Hospitality Research & Development, Dedman School of Hospitality, Florida State University, Tallahassee, FL 32306, USA; [email protected] (D.P.); [email protected] (W.G.K.) 2 College of Hotel and Tourism, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea 3 Center for Converging Humanities, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-2-961-0863 This paper is excerpted from the doctor’s thesis of the first author (2015). y Received: 15 February 2019; Accepted: 18 April 2019; Published: 29 April 2019 Abstract: In order to better understand tourists’ multi-attraction travel behavior, the present study developed a research model by combining the social network analysis technique with the structural equation model. The object of this study was to examine the structural relationships among destination image, tourists’ multi-attraction travel behavior patterns, tourists’ satisfaction, and their behavioral intentions. The data were gathered via an online survey using the China panel system. A total of 468 respondents who visited multiple attractions while in Seoul, Korea, were used for actual analysis. The results showed that all hypotheses are supported. Specifically, destination image was an important antecedent to multi-attraction travel behavior indicated by density and degree indices. In addition, the present study confirmed that density and degree centrality, the indicators of tourists’ multi-attraction travel behavior, were positively related to tourist satisfaction. -
Handbook on Precision Requirements and Variance Estimation for ESS Households Surveys
ISSN 1977-0375 Methodologies and Working papers Handbook on precision requirements and variance estimation for ESS households surveys 2013 edition Methodologies and Working papers Handbook on precision requirements and variance estimation for ESS household surveys 2013 edition Europe Direct is a service to help you find answers to your questions about the European Union. Freephone number (*): 00 800 6 7 8 9 10 11 (*)0H The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you). More information on the European Union is available on the Internet (http://europa.eu). Cataloguing data can be found at the end of this publication. Luxembourg: Publications Office of the European Union, 2013 ISBN 978-92-79-31197-0 ISSN 1977-0375 doi:10.2785/13579 Cat. No: KS-RA-13-029-EN-N Theme: General and regional statistics Collection: Methodologies & Working papers © European Union, 2013 Reproduction is authorised provided the source is acknowledged. Acknowledgments Acknowledgments The European Commission expresses its gratitude and appreciation to the following members of the ESS1 Task Force, for their work on Precision Requirements and Variance Estimation for Household Surveys: Experts from the European Statistical System (ESS): Martin Axelson Sweden — Statistics Sweden Loredana Di Consiglio Italy — ISTAT Kari Djerf Finland — Statistics Finland Stefano Falorsi Italy — ISTAT Alexander Kowarik Austria — Statistics Austria Mārtiņš Liberts Latvia — CSB Ioannis Nikolaidis Greece — EL.STAT Experts from European -
NCRM Social Sciences Research Methods Typology (2014)
NCRM Social Sciences Research Methods Typology (2014) Level 1 Categories Level 2 Subcategories Level 3 Descriptor Terms Frameworks for Research and Research Designs Epistemology Philosophy of social science; Critical theory; Feminist methods; Humanistic methods; Interpretivism; Positivism; Postmodernism; Poststructuralism Descriptive Research Exploratory Research Explanatory Research and Causal analysis Comparative and Cross Cross-national research; National Research Cross-cultural research; Comparative research; Historical comparative research Survey Research Cross-Sectional Research Repeated cross-sections Longitudinal Research Panel survey; Cohort study; Qualitative longitudinal research (QLR); Mixed methods longitudinal research Experimental Research Experimental design; Laboratory studies; Randomized Control Trials (RCT) Quasi-Experimental Research Case-control studies; Difference-in-differences (DID); Paired comparison; Instrumental variables; Regression discontinuity; Twin studies Evaluation Research Policy evaluation; Consumer satisfaction; Theory of change methods Case Study Pilot Study Participatory Research Child-led research; Emancipatory research; Inclusive research; Indigenous methodology; 1 Participatory Action Research (PAR); User engagement Action Research Participatory Action Research (PAR) Ethnographic Research Behavioural Research Meta-Analysis Mantel-Haenszel methods Systematic Review Secondary Analysis Archival research; Documentary research; Analysis of official statistics; Analysis of existing survey data; Analysis -
Assessing Sample Bias and Establishing Standardized
Louisiana State University LSU Digital Commons LSU Master's Theses Graduate School 2003 Assessing sample bias and establishing standardized procedures for weighting and expansion of travel survey data Fahmida Nilufar Louisiana State University and Agricultural and Mechanical College, [email protected] Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_theses Part of the Civil and Environmental Engineering Commons Recommended Citation Nilufar, Fahmida, "Assessing sample bias and establishing standardized procedures for weighting and expansion of travel survey data" (2003). LSU Master's Theses. 1204. https://digitalcommons.lsu.edu/gradschool_theses/1204 This Thesis is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Master's Theses by an authorized graduate school editor of LSU Digital Commons. For more information, please contact [email protected]. ASSESSING SAMPLE BIAS AND ESTABLISHING STANDARDIZED PROCEDURES FOR WEIGHTING AND EXPANSION OF TRAVEL SURVEY DATA A Thesis Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering in The Department of Civil and Environmental Engineering by Fahmida Nilufar B.S., Bangladesh University of Engineering and Technology, 1977 M.S., Bangladesh University of Engineering and Technology, 1985 August 2003 Acknowledgments I would like to express my appreciation to my advisor Dr. Chester Wilmot, for his valuable comments, guidance, support and patience throughout the process. I would also like to thank Dr. Brian Wolshon and Dr. Sherif Ishak for their thoughtful comments on the initial proposal of this work and for consenting to be on my graduate committee.