Self-Report Methods of Jg

Total Page:16

File Type:pdf, Size:1020Kb

Self-Report Methods of Jg If you have issues viewing or accessing this file contact us at NCJRS.gov. National .. ~ Institute on Drug Abuse MONOGRAPH SERIES Self-Report Methods of timating ~ Jg Use I "" ting Current Challenges ~ liclitlf I HUMAN SERVICES • Public Health Service • Alcohol. Drug Abuse. and Mental Health Administration Self-Report Methods of Estimating Drug Use: Meeting Current Challenges to Validity Editors: Beatrice A. Rouse, Ph.D. Nicholas J. Kozel, M.S. Louise G. Richards, Ph.D. Division of Epidemiology and Statistical Analysis National Institute on Drug Abuse NIDA Research Monograph 57 1985 DEPARTMENT OF HEALTH AND HUMAN SERVICES Public Health Service Alcohol, Drug Abuse, and Mental Health Administration National Institute on Drug Abuse 5600 Fishers Lane Rockville, Maryland 20857 For sale uy the Superintendent of Documents, U.S. Government Printing Office Washington, D.C. 20402 NIDA Research Monographs are prepared by the research divisions of the National Institute on Drug Abuse and published by Its Office of Science. The primary objective of the series Is to provide critical reviews of research problem areas and techniques, the content of state-of-the-art conferences, and Integra­ tive research reviews. Its dual publication emphasis Is rapid and targeted dissem­ Ination to the scientific and professional community. Editorial Advisors Martin W. Adler, Ph.D. Temple University School of Medicine Philadelphia, Pennsylvania Sydney Archer, Ph.D. Rensselaer Polytechnic Institute Troy, New Vork R!chard E. Belleville, Ph.D. NB Associates. Health Sciences Rockville. Maryland Gilbert J. Botvin, Ph.D. Cornell University Medical College New Vork. New Vork Joseph V. Brady, Ph.D. The Johns Hopkins University School of Medicine Baltimore. Maryland Theodore J. Cicero, Ph.D. Washington University School of Medicine St. louis, Missouri Sidney Cohen, M.D. ,OS Angeles, California Reese T. Jones, M.D. langley Porter Neuropsychiatric Institute San Francisco. California Denise Kandel, Ph.D. College of Physicians and Surgeons of Columbia University New Vork, New Vork Herbert Kleber, MD. Vale University School of Medicine New Haven. Connecticut· NIDA Research Monograph Series William Pollin, M.D. DIRECTOR. NIDA Jack Durell, M.D. ASSOCIATE DIRECTOR FOR SCIENCE. NIDA EDITOR-iN-CHIEF Eleanor W. Waldrop MANAGING EDITOR Parklawn Building. 5600 Rshers lane, Rockvllle, Maryland 20857 Self-Report Methods of Estimating Drug Use: Meeting Current Challenges to Validity 100257 U.S. Department of Justice National Institute of Justice This document has been reproduced exactly as received from the perslJn 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 of Justice. Permission to reproduce this ~~ material has been .fJranted by Public Dornain~e:?t. of HRALTH & Human Servlces/Nat'I Instltute on Drug Pbuse to the National Criminal Justice Reference Service (NCJRS). Further reproduction outside of the NCJRS system requires permis­ sion of the oopyrigAt.owner. ACKNOWLEDGMENT This monograph is based upon papers presented at a technical review on validity issues in self-reported drug use which took place on May 8 and 9, 1984, at Bethesda, t~aryland. The meeting was sponsored by the Division of Epidemiology and Statistical Analysis, National Institute on Drug Abuse. COPYRIGHT STATUS Material in this volume is in the public domain and may be used or reproduced without permission from the Institute or the authors. Citation of the source is appreciated. Opinions expressed in this volume are those of the authors and do not necessarily reflect the opinions or official policy of the National Institute on Drug Abuse or any other part of the U.S. Department of Health and Human Services. DHHS publication number (ADM)85-1402 Printed 1985 NIOA Research Monographs are indexed in the Index Medicus. They are selectively included in the coverage of American Statistics Index, BioSciences Information Service, Chemical Abstracts, Current contents. Psychological Abstracts, and Psychopharmacology Abstracts. iv PREFACE In many areas of research, including those sponsored by the National Institute on Drug Abuse, the self-report has become an integral component of the research methodology. While there is a growing body of literature that supports the general veridicality of the self-report, there are also studies that suggest under­ reporting in certain populations. This is true of a number of behaviors, including the self-administration of drugs such as tobacco, alcohol, marijuana, cocaine, and heroin. For some behav­ iors which ~re highly stigmatized and/or relatively rare events, such as heroin use, the self-report in sample surveys may not be the most appropriate technique. Thus, methods other than self­ report have been used to estimate the prevalence of heroin addiction. Self-reporting may vary based on the social accept­ ance, or perceived acceptance, of the behavior in question. While the level of stigma associated with heroin use has been constant, there have been sharp reversals in the perception of the accepta­ bility of such behaviors as smoking tobacco, marijuana use, and cocaine use. Shifts in society's attitudes toward these behaviors raise legitimate and necessary questions regarding the continued veridicality of the self-report for these particular behaviors, and it then becomes incumbent upon the researcher to address these issues. This monograph is based, in large part, on a technical review that was held to discuss issues of validity of self­ reported data as well as various estimation techniques. This meeting was another step in a continuing effort designed to main­ tain excellence in the Institute's research in this area and to contribute to the field in general. Edgar H. Adams Acting Director Division of Epidemiology and Statistical Analysis National Institute on Drug Abuse v CONTENTS Preface •.•...••.••.....••.•.... "•...•..•..•.•...•.........•.•• f v Introducti9n and Overview, ••........•.•• ~i.~~.~~..... 1 Beatr'LCe A. Rouse, Nu::hoZas J. KouJft",'fl ~~~ ~1Sr'~ and Louise G. Richards A DlSCUSSlon· . 0 f Vall l' d . t y ................'~~ n~J~ ...~,pr.,.I" '......... 4 David N. Nurao - . Validation of Self-Report: The Res~~~\P:f~~·rJS. 12 Adele V. HarreU Influence of Privacy on Self-Reported Drug Use by Youths 22 Joseph Gfroerer Issues of Validity and Population Coverage in Student Surveys of Drug Use .••••....•.••.•......•..•.•.••.••.••.••.•• 31 Lloyd D. Johnston and Patrick M. O'MaUey Sampling and Coverage Difficulties in Canadian Drug Use Surveys and Efforts to Avoid Them •..••••.•••.....•.••..•.•.•. 55 Reginald G. Smart Dynamic Simulation Models: How Valid Are They? ••.•..••.••••• 63 Raymond c. Shreckengost Telephone Surveying for Drug Abuse: Methodological Issues and an APRl ication .•......•••..••.•.•..•...••...••.•...•.. , .• 71 Blanche Frank A Pilot Study Assessing Maternal Marijuana Use by Urine Assay During Pregnancy ..•.••.••..•...•••.••.•.••.••.••.••..•. 84 Barry S. Zuckerman, Ralph W. Hingson, Suzette MoreLock, Hortensia Amaro, Deborah Frank, James R. Sorenson, Herbert L. Kayne, and Ralph Timperi History of Heroin Prevalence Estimation Techniques •.••.....•. 94 Marc D. Brod sky vii Preceding page blank The Nominative Technique: A New Method of Estimating Heroin Preva'ence ••••••••••••••••••••••••••• ~................ ••••••• 104 Judith DPoitcour Mitter Heroin Incidence: A Trend Comparison Between National Household Survey Data and Indicator Data..................... 125 Raquet A. Crider Estimating Heroin Imports into the United States............. 141 Keith L. Gardiner and Raymond C. Shreckengost Estimating the Size of a Heroin-Abusing Population Using Multiple-Recapture Census.................................... 158 J. Arthur Woodward~ Dougtas G. Bonett~ and M.L. Brecht Participants................................................. 172 List of Monographs..... 175 viii INTRODUCTION AND OVERVIEW Beatrice A. Rouse, Nicholas J. Kozel Louise G. Richards Various methods of identifying drug users have been developed to improve or validate estimates based on direct questioning of individuals regarding their use of drugs. These methods include biochemical analysis of different body fluids, indirect question­ ing techniques, and statistical modeling procedures. Examples of each of these methods are included in this volume. Chapters in this volume are the product of a National Institute on Drug Abuse (NIDA) Technical Review convened to examine various methodological issues regarding the validity of self-report data. The meeting was held May 8-9, 1984, at the National Institutes of Health. While validity covers a wide range of methodological concerns, the Technical Review participants focused on three areas: 1) under­ reporting of drug use on direct questioning, 2) noncoverage of groups in the population who are at risk, and 3) procedures for estimating low prevalence drugs, such as heroin. The papers presented in this volume attest to the rich array of concepts, methods, empirical results, and evaluations engendered by the meeting. In the first chapter, Nurco identifies and describes the different types of validity, raises various validity issues in drug use and crime research, and suggests strategies for improving the validity of self-report data. Harrell reiterates the fact that validity is a multidimensional concept and discusses those research conditions and respondent characteristics found in methodological research
Recommended publications
  • Background to the Celebration of Herbert D. Kleber (1904 -2018) by Thomas A
    1 Background to the Celebration of Herbert D. Kleber (1904 -2018) by Thomas A. Ban By the mid-1990s the pioneering generation in neuropsychopharmacology was fading away. To preserve their legacy the late Oakley Ray (1931-2007), at the time Secretary of the American College of Neuropsychopharmacology (ACNP), generated funds from Solway Pharmaceuticals for the founding of the ACNP-Solway Archives in Neuropsychopharmacology. Ray also arranged for the videotaping of interviews (mainly by their peers) with the pioneers, mostly at annual meetings, to be stored in the archives. Herbert Kleber was interviewed by Andrea Tone, a medical historian at the Annual Meeting of the College held in San Juan, Puerto Rico, on December 7, 2003 (Ban 2011a; Kleber 2011a). The endeavor that was to become known as the “oral history project” is based on 235 videotaped interviews conducted by 66 interviewers with 213 interviewees which, on the basis of their content, were divided and edited into a 10-volume series produced by Thomas A. Ban, in collaboration with nine colleagues who were to become volume editors. One of them, Herbert Kleber, was responsible for the editing of Volume Six, dedicated to Addiction (Kleber 2011b). The series was published by the ACNP with the title “An Oral History of Neuropsychopharmacology Peer Interviews The First Fifty Years” and released at the 50th Anniversary Meeting of the College in 2011 (Ban 2011b). Herbert Daniel Kleber was born January 19, 1934, in Pittsburgh, Pennsylvania. His family’s father’s side was from Vilnius, Lithuania, and the Mother’s side was from Germany. Both families came to the United State during the first decade of the 20th century.
    [Show full text]
  • Downloads Automatically
    VIRGINIA LAW REVIEW ASSOCIATION VIRGINIA LAW REVIEW ONLINE VOLUME 103 DECEMBER 2017 94–102 ESSAY ACT-SAMPLING BIAS AND THE SHROUDING OF REPEAT OFFENDING Ian Ayres, Michael Chwe and Jessica Ladd∗ A college president needs to know how many sexual assaults on her campus are caused by repeat offenders. If repeat offenders are responsible for most sexual assaults, the institutional response should focus on identifying and removing perpetrators. But how many offenders are repeat offenders? Ideally, we would find all offenders and then see how many are repeat offenders. Short of this, we could observe a random sample of offenders. But in real life, we observe a sample of sexual assaults, not a sample of offenders. In this paper, we explain how drawing naive conclusions from “act sampling”—sampling people’s actions instead of sampling the population—can make us grossly underestimate the proportion of repeat actors. We call this “act-sampling bias.” This bias is especially severe when the sample of known acts is small, as in sexual assault, which is among the least likely of crimes to be reported.1 In general, act sampling can bias our conclusions in unexpected ways. For example, if we use act sampling to collect a set of people, and then these people truthfully report whether they are repeat actors, we can overestimate the proportion of repeat actors. * Ayres is the William K. Townsend Professor at Yale Law School; Chwe is Professor of Political Science at the University of California, Los Angeles; and Ladd is the Founder and CEO of Callisto. 1 David Cantor et al., Report on the AAU Campus Climate Survey on Sexual Assault and Sexual Misconduct, Westat, at iv (2015) [hereinafter AAU Survey], (noting that a relatively small percentage of the most serious offenses are reported) https://perma.cc/5BX7-GQPU; Nat’ Inst.
    [Show full text]
  • Human Dimensions of Wildlife the Fallacy of Online Surveys: No Data Are Better Than Bad Data
    Human Dimensions of Wildlife, 15:55–64, 2010 Copyright © Taylor & Francis Group, LLC ISSN: 1087-1209 print / 1533-158X online DOI: 10.1080/10871200903244250 UHDW1087-12091533-158XHuman Dimensions of WildlifeWildlife, Vol.The 15, No. 1, November 2009: pp. 0–0 Fallacy of Online Surveys: No Data Are Better Than Bad Data TheM. D. Fallacy Duda ofand Online J. L. Nobile Surveys MARK DAMIAN DUDA AND JOANNE L. NOBILE Responsive Management, Harrisonburg, Virginia, USA Internet or online surveys have become attractive to fish and wildlife agencies as an economical way to measure constituents’ opinions and attitudes on a variety of issues. Online surveys, however, can have several drawbacks that affect the scientific validity of the data. We describe four basic problems that online surveys currently present to researchers and then discuss three research projects conducted in collaboration with state fish and wildlife agencies that illustrate these drawbacks. Each research project involved an online survey and/or a corresponding random telephone survey or non- response bias analysis. Systematic elimination of portions of the sample population in the online survey is demonstrated in each research project (i.e., the definition of bias). One research project involved a closed population, which enabled a direct comparison of telephone and online results with the total population. Keywords Internet surveys, sample validity, SLOP surveys, public opinion, non- response bias Introduction Fish and wildlife and outdoor recreation professionals use public opinion and attitude sur- veys to facilitate understanding their constituents. When the surveys are scientifically valid and unbiased, this information is useful for organizational planning. Survey research, however, costs money.
    [Show full text]
  • Levy, Marc A., “Sampling Bias Does Not Exaggerate Climate-Conflict Claims,” Nature Climate Change 8,6 (442)
    Levy, Marc A., “Sampling bias does not exaggerate climate-conflict claims,” Nature Climate Change 8,6 (442) https://doi.org/10.1038/s41558-018-0170-5 Final pre-publication text To the Editor – In a recent Letter, Adams et al1 argue that claims regarding climate-conflict links are overstated because of sampling bias. However, this conclusion rests on logical fallacies and conceptual misunderstanding. There is some sampling bias, but it does not have the claimed effect. Suggesting that a more representative literature would generate a lower estimate of climate- conflict links is a case of begging the question. It only make sense if one already accepts the conclusion that the links are overstated. Otherwise it is possible that more representative cases might lead to stronger estimates. In fact, correcting sampling bias generally does tend to increase effect estimates2,3. The authors’ claim that the literature’s disproportionate focus on Africa undermines sustainable development and climate adaptation rests on the same fallacy. What if the climate-conflict links are as strong as people think? It is far from obvious that acting as if they were not would somehow enhance development and adaptation. The authors offer no reasoning to support such a claim, and the notion that security and development are best addressed in concert is consistent with much political theory and practice4,5,6. Conceptually, the authors apply a curious kind of “piling on” perspective in which each new paper somehow ratchets up the consensus view of a country’s climate-conflict links, without regard to methods or findings. Consider the papers cited as examples of how selecting cases on the conflict variable exaggerates the link.
    [Show full text]
  • 10. Sample Bias, Bias of Selection and Double-Blind
    SEC 4 Page 1 of 8 10. SAMPLE BIAS, BIAS OF SELECTION AND DOUBLE-BLIND 10.1 SAMPLE BIAS: In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others. It results in abiased sample, a non-random sample[1] of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected.[2] If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling. Medical sources sometimes refer to sampling bias as ascertainment bias.[3][4] Ascertainment bias has basically the same definition,[5][6] but is still sometimes classified as a separate type of bias Types of sampling bias Selection from a specific real area. For example, a survey of high school students to measure teenage use of illegal drugs will be a biased sample because it does not include home-schooled students or dropouts. A sample is also biased if certain members are underrepresented or overrepresented relative to others in the population. For example, a "man on the street" interview which selects people who walk by a certain location is going to have an overrepresentation of healthy individuals who are more likely to be out of the home than individuals with a chronic illness. This may be an extreme form of biased sampling, because certain members of the population are totally excluded from the sample (that is, they have zero probability of being selected).
    [Show full text]
  • Cognitive Biases in Software Engineering: a Systematic Mapping Study
    Cognitive Biases in Software Engineering: A Systematic Mapping Study Rahul Mohanani, Iflaah Salman, Burak Turhan, Member, IEEE, Pilar Rodriguez and Paul Ralph Abstract—One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently gained popularity in software engineering research. This paper therefore systematically maps, aggregates and synthesizes the literature on cognitive biases in software engineering to generate a comprehensive body of knowledge, understand state of the art research and provide guidelines for future research and practise. Focusing on bias antecedents, effects and mitigation techniques, we identified 65 articles (published between 1990 and 2016), which investigate 37 cognitive biases. Despite strong and increasing interest, the results reveal a scarcity of research on mitigation techniques and poor theoretical foundations in understanding and interpreting cognitive biases. Although bias-related research has generated many new insights in the software engineering community, specific bias mitigation techniques are still needed for software professionals to overcome the deleterious effects of cognitive biases on their work. Index Terms—Antecedents of cognitive bias. cognitive bias. debiasing, effects of cognitive bias. software engineering, systematic mapping. 1 INTRODUCTION OGNITIVE biases are systematic deviations from op- knowledge. No analogous review of SE research exists. The timal reasoning [1], [2]. In other words, they are re- purpose of this study is therefore as follows: curring errors in thinking, or patterns of bad judgment Purpose: to review, summarize and synthesize the current observable in different people and contexts. A well-known state of software engineering research involving cognitive example is confirmation bias—the tendency to pay more at- biases.
    [Show full text]
  • Correcting Sampling Bias in Non-Market Valuation with Kernel Mean Matching
    CORRECTING SAMPLING BIAS IN NON-MARKET VALUATION WITH KERNEL MEAN MATCHING Rui Zhang Department of Agricultural and Applied Economics University of Georgia [email protected] Selected Paper prepared for presentation at the 2017 Agricultural & Applied Economics Association Annual Meeting, Chicago, Illinois, July 30 - August 1 Copyright 2017 by Rui Zhang. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies. Abstract Non-response is common in surveys used in non-market valuation studies and can bias the parameter estimates and mean willingness to pay (WTP) estimates. One approach to correct this bias is to reweight the sample so that the distribution of the characteristic variables of the sample can match that of the population. We use a machine learning algorism Kernel Mean Matching (KMM) to produce resampling weights in a non-parametric manner. We test KMM’s performance through Monte Carlo simulations under multiple scenarios and show that KMM can effectively correct mean WTP estimates, especially when the sample size is small and sampling process depends on covariates. We also confirm KMM’s robustness to skewed bid design and model misspecification. Key Words: contingent valuation, Kernel Mean Matching, non-response, bias correction, willingness to pay 2 1. Introduction Nonrandom sampling can bias the contingent valuation estimates in two ways. Firstly, when the sample selection process depends on the covariate, the WTP estimates are biased due to the divergence between the covariate distributions of the sample and the population, even the parameter estimates are consistent; this is usually called non-response bias.
    [Show full text]
  • Quantifying Aristotle's Fallacies
    mathematics Article Quantifying Aristotle’s Fallacies Evangelos Athanassopoulos 1,* and Michael Gr. Voskoglou 2 1 Independent Researcher, Giannakopoulou 39, 27300 Gastouni, Greece 2 Department of Applied Mathematics, Graduate Technological Educational Institute of Western Greece, 22334 Patras, Greece; [email protected] or [email protected] * Correspondence: [email protected] Received: 20 July 2020; Accepted: 18 August 2020; Published: 21 August 2020 Abstract: Fallacies are logically false statements which are often considered to be true. In the “Sophistical Refutations”, the last of his six works on Logic, Aristotle identified the first thirteen of today’s many known fallacies and divided them into linguistic and non-linguistic ones. A serious problem with fallacies is that, due to their bivalent texture, they can under certain conditions disorient the nonexpert. It is, therefore, very useful to quantify each fallacy by determining the “gravity” of its consequences. This is the target of the present work, where for historical and practical reasons—the fallacies are too many to deal with all of them—our attention is restricted to Aristotle’s fallacies only. However, the tools (Probability, Statistics and Fuzzy Logic) and the methods that we use for quantifying Aristotle’s fallacies could be also used for quantifying any other fallacy, which gives the required generality to our study. Keywords: logical fallacies; Aristotle’s fallacies; probability; statistical literacy; critical thinking; fuzzy logic (FL) 1. Introduction Fallacies are logically false statements that are often considered to be true. The first fallacies appeared in the literature simultaneously with the generation of Aristotle’s bivalent Logic. In the “Sophistical Refutations” (Sophistici Elenchi), the last chapter of the collection of his six works on logic—which was named by his followers, the Peripatetics, as “Organon” (Instrument)—the great ancient Greek philosopher identified thirteen fallacies and divided them in two categories, the linguistic and non-linguistic fallacies [1].
    [Show full text]
  • Thesis with Row Frequencies (RF) and Column Frequencies (CF)………………………...173
    SAMPLING BIASES AND NEW WAYS OF ADDRESSING THE SIGNIFICANCE OF TRAUMA IN NEANDERTALS by Virginia Hutton Estabrook A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Anthropology) in The University of Michigan 2009 Doctoral Committee: Professor Milford H. Wolpoff, Chair Professor A. Roberto Frisancho Professor John D. Speth Associate Professor Thomas R. Gest Associate Professor Rachel Caspari, Central Michigan University © Virginia Hutton Estabrook 2009 To my father who read to me my first stories of prehistory ii ACKNOWLEDGEMENTS There are so many people whose generosity and inspiration made this dissertation possible. Chief among them is my husband, George Estabrook, who has been my constant cheerleader throughout this process. I would like to thank my committee for all of their help, insight, and time. I am truly fortunate in my extraordinary advisor and committee chair, Milford Wolpoff, who has guided me throughout my time here at Michigan with support, advice, and encouragement (and nudging). I am deeply indebted to Tom Gest, not only for being a cognate par excellence, but also for all of his help and attention in teaching me gross anatomy. Rachel Caspari, Roberto Frisancho, and John Speth gave me their attention for this dissertation and also offered me wonderful examples of academic competence, graciousness, and wit when I had the opportunity to take their classes and/or teach with them as their GSI. All photographs of the Krapina material, regardless of photographer, are presented with the permission of J. Radovčić and the Croatian Natural History Museum. My research would not have been possible without generous grants from Rackham, the International Institute, and the Department of Anthropology.
    [Show full text]
  • HEHS-96-80 Cocaine Treatment Outcomes B-265688
    United States General Accounting Office GAO Report to Congressional Requesters June 1996 COCAINE TREATMENT Early Results From Various Approaches GOA years 1921 - 1996 GAO/HEHS-96-80 United States General Accounting Office GAO Washington, D.C. 20548 Health, Education, and Human Services Division B-265688 June 7, 1996 The Honorable William F. Clinger, Jr. Chairman The Honorable Cardiss Collins Ranking Minority Member Committee on Government Reform and Oversight House of Representatives The Honorable Henry A. Waxman House of Representatives Cocaine use in the United States remains a serious and costly epidemic. In 1994, the National Household Survey on Drug Abuse conservatively estimated that more than three-quarters of a million people had used cocaine at least once a week within the past year. In 1993, cocaine was associated with almost 4,000 deaths.1 Today, an estimated $10 billion per year is lost in cocaine-related crimes and productivity.2 Although cocaine admissions to state-supported drug abuse treatment programs between 1985 and 1990 increased dramatically—from almost 39,000 people to more than 200,000—we found in 1991 that an effective treatment for cocaine addiction had not yet been identified.3 Today, public/private expenditures on cocaine-related treatment total about $1 billion per year. Because of cocaine’s serious health, economic, and criminal justice implications for the nation, we have provided a status report on recent progress made in finding an effective treatment for cocaine users.4 Specifically, we reviewed the various types of federally funded treatment approaches evaluated over the past 5 years (1991 through 1995) to (1) determine the extent to which these therapies have proven successful and (2) identify additional research initiatives necessary to increase our knowledge of cocaine treatment effectiveness.
    [Show full text]
  • New Techniques for Time-Activity Studies of Avian Flocks in View-Restricted Habitats
    j. Field Ornithol., 60(3):388-396 NEW TECHNIQUES FOR TIME-ACTIVITY STUDIES OF AVIAN FLOCKS IN VIEW-RESTRICTED HABITATS MICHAEL P. LOSITO,• RALPH E. MIRARCHI, AND GUY A. BALDASSARRE 1 Departmentof Zoologyand WildlifeScience AlabamaAgricultural Experiment Station Auburn University,Alabama 36849-5414 USA Abstract.--Focal-animal sampling was comparedto a newly developedtechnique, focal- switchsampling, to evaluatetime budgetsof Mourning Doves(Zenaida macroura) in habitats where the field of view was restricted.Focal-switch sampling included a formula employed to weighthabitat use and testfor restrictionsof habitatstructure on behavior,and a standard waiting period to decidewhen to end sampling or continue pursuit of lost flocks. Focal- animal samplingbiased estimates of activebehavior downward, whereas estimates of inactive behaviorwere similar for both methods.Focal-switch sampling increased research efficiency by 12%. The standardwaiting period saved24% of samplesfrom prematuretermination and reducedobserver bias by maintaining equal sampling effort per flock. Weighting of habitat use also reducedsampling bias. Focal-switch sampling is recommendedfor use in conjunctionwith focal-animalsampling when samplingin view-restrictedhabitats. NUEVAS TP•CNICASPARA EL ESTUDIO DE ACTIVIDADES DE CONGREGACIONES DE AVES EN HABITATS CON VISIBILIDAD RESTRINGIDA Resumen.--Lat6cnica de observaci6ndirecta de animales(focal-animal) es comparada con un nuevom6todo en dondese evaluan los presupuestosde actividadesen Zenaidamacroura en habitatsen dondeel campode visi6nestaba restringido. La nuevat6cnica (cambio-focal) incluyeuna f6rmulapara "pesar"la utilizaci6nde habitaty medirlas restriccionesque imponenla estructuradel habitaten la conducta.Incluye ademfis,un periodode espera estandarizadoque permite al observadordecidir cuando terminar susobservaciones o conti- nuar las mismas.E1 muestreo de un soloanimal (focal-animal)tiene un sesgopara estimar la conductaactira, mientras que los estimados para conducta inactiva rueton similares para ambosm6todos.
    [Show full text]
  • 730 Philosophy 101, Sect 01 Logic, Reason and Persuasion
    730 Philosophy101, Sect 01 Logic, Reason and Persuasion Instructor: SidneyFelder,e-mail: [email protected] Rutgers The State University of NewJersey, Fall 2009, Tu&Th2:15-3:35, TH-206 I. Fundamental Philosophical Terms and Concepts of Language (week 1) Extension and Intension; Puzzles of Identity and Reference; Types and Tokens; Language and Metalanguage; Logical Paradoxes. Course Notes: Fundamental Terms and Concepts of Language.Schaum’s pps. 16-17 II. Elements of Set Theory (weeks 1, 2 and 3) Sets and Subsets. Union, Intersection, and Complementation. Ordered Pairs, Cartesian Products; Relations, Functions. Equivalence Relations. Denumerable and Non-denumerable Infinite Sets. Course Notes: Elements of Set Theory. III. Linear and Partial Orderings (weeks 3 and 4) Linear Orderings; Partial Orderings. Upper Bounds and Lower Bounds; Least Upper and Greatest Lower Bounds. Course Notes: Linear and Partial Orderings. IV.Truth-Functional Propositional Logic (weeks 4, 5, and 6) Symbolism. The Logical Constants. Logical Implication and Equivalence. Consistency, Satisfiability,and Validity. Course Notes: Truth Functional Propositional Logic. Schaum’s pps. 44-68 V. Quantification (weeks 6and 7) ‘All’ and ‘There exists’ — The universal and existential quantifiers. Free and Bound variables; Open and Closed Formulæ (Sentences). Interpretations and Models; Number. Logical Strength. Course Notes: Quantification Logic. Schaum’s ch. 5; ch. 6 pps. 130-149; ch. 9 pps. 223-226 Midterm VI. Fallacies (week 8) Strawman. Ad Hominem;Argument from Authority; Arguments from Pervasiveness of Belief. Arguments from Absence of Information. Schaum’s ch. 8 Syllabus Page 1 Philosophy101, Sect 01 Logic, Reason and Persuasion VII. Probability and Statistical Arguments (weeks 9 and 10) Elements of Axiomatic Probability.
    [Show full text]