Estimating the size of an illicit-drug-using population
This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of registry‐based techniques that require both comprehensive site coverage and unique case identifiers, and which do not typically provide estimates of the nu...
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Published in | Statistics in medicine Vol. 22; no. 19; pp. 2969 - 2993 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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Chichester, UK
John Wiley & Sons, Ltd
15.10.2003
Wiley |
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Abstract | This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of registry‐based techniques that require both comprehensive site coverage and unique case identifiers, and which do not typically provide estimates of the number of drug users who are currently active. The approach involves collecting retrospective self‐report data on the careers of individuals who appear at drug treatment programmes. A model is developed that corrects for the selection bias introduced by the sampling plan, and which allows us to estimate the rate at which drug users generate treatment admission events during spells of use. The size of the drug‐using population is estimated by dividing the estimated total number of treatment admissions that are generated during some fixed interval of time by the estimated rate at which individuals generate such events. The technique is tested in a series of simulation studies which demonstrate that accurate estimates of the size of the drug using population can be obtained in this manner. Analytical expressions for confidence intervals about the population estimates are derived as part of the exercise. Limitations of the approach and other potential applications are discussed. Copyright © 2003 John Wiley & Sons, Ltd. |
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AbstractList | Abstract
This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of registry‐based techniques that require both comprehensive site coverage and unique case identifiers, and which do not typically provide estimates of the number of drug users who are currently active. The approach involves collecting retrospective self‐report data on the careers of individuals who appear at drug treatment programmes. A model is developed that corrects for the selection bias introduced by the sampling plan, and which allows us to estimate the rate at which drug users generate treatment admission events during spells of use. The size of the drug‐using population is estimated by dividing the estimated total number of treatment admissions that are generated during some fixed interval of time by the estimated rate at which individuals generate such events. The technique is tested in a series of simulation studies which demonstrate that accurate estimates of the size of the drug using population can be obtained in this manner. Analytical expressions for confidence intervals about the population estimates are derived as part of the exercise. Limitations of the approach and other potential applications are discussed. Copyright © 2003 John Wiley & Sons, Ltd. This paper describes a new method for estimating the size of an illicit-drug-using population. It is designed to overcome certain limitations of registry-based techniques that require both comprehensive site coverage and unique case identifiers, and which do not typically provide estimates of the number of drug users who are currently active. The approach involves collecting retrospective self-report data on the careers of individuals who appear at drug treatment programmes. A model is developed that corrects for the selection bias introduced by the sampling plan, and which allows us to estimate the rate at which drug users generate treatment admission events during spells of use. The size of the drug-using population is estimated by dividing the estimated total number of treatment admissions that are generated during some fixed interval of time by the estimated rate at which individuals generate such events. The technique is tested in a series of simulation studies which demonstrate that accurate estimates of the size of the drug using population can be obtained in this manner. Analytical expressions for confidence intervals about the population estimates are derived as part of the exercise. Limitations of the approach and other potential applications are discussed. This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of registry‐based techniques that require both comprehensive site coverage and unique case identifiers, and which do not typically provide estimates of the number of drug users who are currently active. The approach involves collecting retrospective self‐report data on the careers of individuals who appear at drug treatment programmes. A model is developed that corrects for the selection bias introduced by the sampling plan, and which allows us to estimate the rate at which drug users generate treatment admission events during spells of use. The size of the drug‐using population is estimated by dividing the estimated total number of treatment admissions that are generated during some fixed interval of time by the estimated rate at which individuals generate such events. The technique is tested in a series of simulation studies which demonstrate that accurate estimates of the size of the drug using population can be obtained in this manner. Analytical expressions for confidence intervals about the population estimates are derived as part of the exercise. Limitations of the approach and other potential applications are discussed. Copyright © 2003 John Wiley & Sons, Ltd. |
Author | Holland, Lynn Viveros-Aguilero, Roman Simeone, Ronald |
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Cites_doi | 10.1046/j.1360-0443.2000.951217959.x 10.1177/002204269302300204 10.1177/002204269302300206 10.1177/002204269902900112 10.1016/0740-5472(92)90062-S 10.1002/sim.996 10.1177/0193841X9802200404 10.1177/0193841X9301700107 10.1037/0893-164X.11.4.308 10.1016/S0740-5472(97)00016-0 10.1007/978-1-4899-4541-9 10.15288/jsa.1988.49.225 10.1081/ADA-100101868 10.3109/10826089509048751 10.2307/271044 10.2307/1912352 10.1177/002204269302300210 10.3109/10826087709027233 10.1002/(SICI)1097-0320(20000401)39:4<300::AID-CYTO8>3.0.CO;2-O 10.2139/ssrn.304926 |
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Studies on Alcohol – volume: 11 start-page: 308 year: 1997 end-page: 323 article-title: Drug addiction and treatment careers among clients in the Drug Abuse Treatment Outcome Study (DATOS) publication-title: Psychology of Addictive Behaviors – volume: 57 start-page: 158 year: 1985 end-page: 170 article-title: Estimating the size of a heroin‐abusing population using multiple‐recapture census publication-title: NIDA Monograph Series – year: 1996 – year: 1992 – year: 1994 – volume: 47 start-page: 153 year: 1979 end-page: 162 article-title: Sample selection bias as a specification error publication-title: Econometrica – volume: 22 start-page: 496 year: 1998 end-page: 519 article-title: Relationships between drug treatment careers and outcomes: Findings from the National Drug Abuse Treatment Outcome Study publication-title: Evaluation Review – volume: 14 start-page: 543 year: 1997 end-page: 558 article-title: Drug treatment careers: a conceptual framework and existing research findings 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Snippet | This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of registry‐based... This paper describes a new method for estimating the size of an illicit-drug-using population. It is designed to overcome certain limitations of registry-based... Abstract This paper describes a new method for estimating the size of an illicit‐drug‐using population. It is designed to overcome certain limitations of... |
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SubjectTerms | Bias Biological and medical sciences Chicago - epidemiology Humans illicit drug use Medical sciences Models, Statistical Patient Acceptance of Health Care - statistics & numerical data Population Surveillance ratio estimation sample selection bias simulation Substance Abuse Treatment Centers - utilization Substance-Related Disorders - epidemiology |
Title | Estimating the size of an illicit-drug-using population |
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