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Quality Control and Good Epidemiological Practice

  • Chapter
Handbook of Epidemiology

Abstract

The use of data is fundamental in epidemiology. Epidemiologic research on causation uses data in a search for the true nature of the relationship between exposure and disease. Similarly, research on the consequences of interventions seeks an unbiased characterization of the effects of independently varying factors on the outcome measure(s). One of the most rewarding moments for a researcher is obtaining the preliminary results from his or her study. However, the question “do I believe what I see?” should immediately come to mind. The answer to this question is determined in large part by the more mundane but critical question of how good is the quality of the data, rather than by the elegance of the scientific method. Errors that occur during study population selection or in the measurement of study exposures, outcomes, or covariates can lead to a biased estimate of the effect of exposure on risk for the disease of interest. Misclassification of exposure or disease that occurs randomly between all study participants decreases the power of the study to detect an association where it exists. Data collection that is differentially biased may have more severe consequences, and can lead to an incorrect assessment of the relationship between exposure and disease.

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References

  • Agresti A (1990) Categorical data analysis. John Wiley and Sons, Hoboken, NJ

    MATH  Google Scholar 

  • Altman D, Bland J (1983) Measurements in medicine: the analysis of method comparison studies. Statistician 32:307–317

    Article  Google Scholar 

  • American Association for Public Opinion Research. Standard definitions (2000) Final dispositions of case codes and outcome rates for surveys. American Association for Public Opinion Research, Ann Arbor, MI

    Google Scholar 

  • Armstrong B, White E (1992) Principles of exposure measurement in epidemiology. Oxford University Press, New York

    Google Scholar 

  • Arts DG, De Keizer NF, Scheffer GJ (2002) Defining and improving data quality in medical registries: a literature review, case study, and generic framework. J Am Med Inform Assoc 9:600–611

    Article  Google Scholar 

  • Asch DA, Jedrziewski MK, Christakis NA (1997) Response rates to mail surveys published in medical journals. J Clin Epidemiol 50:1129–1136

    Article  Google Scholar 

  • Asch DA, Christakis NA, Ubel PA (1998) Conducting physician mail surveys on a limited budget. A randomized trial comparing $2 bill versus $5 bill incentives. Med Care 36:95–99

    Article  Google Scholar 

  • Ascherio A, Stampfer MJ, Colditz GA, Rimm EB, Litin L, Willet WC (1992) Correlations of vitamin A and E intakes with the plasma concentrations of carotenoids and tocopherols among American men and women. J Nutr 122: 1792–1801

    Google Scholar 

  • Baer A, Saroiu S, Koutsky LA (2002) Obtaining sensitive data through the Web: an example of design and methods. Epidemiol 13:640–645

    Article  Google Scholar 

  • Barnett V, Lewis T (1994) Outliers in statistical data. John Wiley and Sons, Hoboken, N.J.

    MATH  Google Scholar 

  • Berkanovic E (1980) The effect of inadequate language translation on Hispanics’ responses to health surveys. Am J Public Health 80:1273–1276

    Google Scholar 

  • Bisgard KM, Folsom AR, Hong CP, Sellers TA (1994) Mortality and cancer rates in nonrespondents to a prospective study of older women: 5-year follow-up. Am J Epidemiol 139:990–1000

    Google Scholar 

  • Blackmore CC, Richardson ML, Linnau KF, Schwed AM, Lomoschitz FM, Escobedo EM, Hunter JC, Jurkovich GJ, Cummings P (2003) Web-based image review and data acquisition form ultiinstitutional research. AJR Am J Roentgenol 180:1243–1246

    Google Scholar 

  • Brenner H, Gefeller O (1997) Variation of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence. Stat Med 16:981–991

    Article  Google Scholar 

  • Breslow N, Day N (1980) Statistical methods in cancer research. Volume I — The analysis of case-control studies. International Agency for Research on Cancer, Lyon

    Google Scholar 

  • Breslow N, Day N (1987) Statistical methods in cancer research. Volume II — The design and analysis of cohort studies. International Agency for Research on Cancer, Lyon

    Google Scholar 

  • Bryant AH, Reinert A (2001) Epidemiology in the legal arena and the search for truth. Am J Epidemiol 154:S27–S35

    Article  Google Scholar 

  • Canner PL, Krol WF, Forman SA (1983) The Coronary Drug Project. External quality control programs. Control Clin Trials 4:441–466

    Article  Google Scholar 

  • Canner PL, Borhani NO, Oberman A, Cutler J, Prineas RJ, Langford H, Hooper FJ (1991) The Hypertension Prevention Trial: assessment of the quality of blood pressure measurements. Am J Epidemiol 134:379–392

    Google Scholar 

  • Centers for Disease Control and Prevention (CDC) (1999) BRFSS summary quality control report. Centers for Disease Control and Prevention, Atlanta, GA

    Google Scholar 

  • Cherrie J, Schneider T (1998) Validation of a new method for structured subjective assessment of past concentrations. Annals Occup Hyg 43:235–245

    Google Scholar 

  • Cherrie J, Krantz S, Schneider T, Ohberg I, Kamstrup O, Linander W (1987) An experimental simulation of an early rock wool/slag wool production process. Ann Occup Hyg 31:583–593

    Article  Google Scholar 

  • Choi BC, Pak AW, Purdham JT (1990) Effects of mailing strategies on response rate, response time, and cost in a questionnaire study among nurses. Epidemiol 1:72–74

    Article  Google Scholar 

  • Christiansen DH, Hosking JD, Dannenberg AL, Williams OD (1990) Computer-assisted data collection in multicenter epidemiologic research. The Atherosclerosis Risk in Communities Study. Control Clin Trials 11:101–115

    Article  Google Scholar 

  • Cicchetti DV, Feinstein AR (1990) High agreement but low kappa: II. Resolving the paradoxes. J Clin Epidemiol 43:551–558

    Article  Google Scholar 

  • Clement DL, De Buyzere ML, De Bacquer DA, de Leeuw PW, Duprez DA, Fagard RH, Gheeraert PJ, Missault LH, Braun JJ, Six RO, Van Der NP, O’Brien E (2003) Prognostic value of ambulatory blood-pressure recordings in patients with treated hypertension. N Engl J Med 348:2407–2415

    Article  Google Scholar 

  • Clive RE, Ocwieja KM, Kamell L, Hoyler SS, Seiffert JE, Young JL, Henson DE, Winchester DP, Osteen RT, Menck HR (1995) A national quality improvement effort: cancer registry data. J Surg Oncol 58:155–161

    Article  Google Scholar 

  • Cohen J (1968) Weighted kappa: nominal scale agreement with provision for scaled disagreement of partial credit. Psychological Bulletin 70:213–220

    Article  Google Scholar 

  • Collins RL, Ellickson PL, Hays RD, McCaffrey DF (2000) Effects of incentive size and timing on response rates to a follow-up wave of a longitudinal mailed survey. Eval Rev 24:347–363

    Google Scholar 

  • Comstock GW, Tockman MS, Helsing KJ, Hennesy KM (1979) Standardized respiratory questionnaires: comparison of the old with the new. Am Rev Respir Dis 119:45–53

    Google Scholar 

  • Cook RR (1991) Overview of good epidemiologic practices. J Occup Med 33: 1216–1220

    Google Scholar 

  • Cooper GR (1986) The importance of quality control in the Multiple Risk Factor Intervention Trial. Control Clin Trials 7:3pp

    Google Scholar 

  • Cottler LB, Zipp JF, Robins LN, Spitznagel EL (1987) Difficult-to-recruit respondents and their effect on prevalence estimates in an epidemiologic survey. Am J Epidemiol 125:329–339

    Google Scholar 

  • Crombie IK, Irving JM (1986) An investigation of data entry methods with a personal computer. Comput Biomed Res 19:543–550

    Article  Google Scholar 

  • Dawber TR, Meadors GF, Moore FE, Jr. (1951) Epidemiological approaches to heart disease: The Framingham Study. Am J Public Health 41:279–286

    Google Scholar 

  • Day S, Fayers P, Harvey D (1998) Double data entry: what value, what price? Control Clin Trials 19:15–24

    Article  Google Scholar 

  • Deyo RA, Diehr P, Patrick DL (1991) Reproducibility and responsiveness of health status measures. Statistics and strategies for evaluation. Control Clin Trials 12:142S–158S

    Article  Google Scholar 

  • Dillman D (1978) Mail and telephone surveys: the total design method. John Wiley and Sons, New York

    Google Scholar 

  • Dischinger P, DuChene AG (1986) Quality control aspects of blood pressure measurements in the Multiple Risk Factor Intervention Trial. Control Clin Trials 7:137S–157S

    Article  Google Scholar 

  • Doody MM, Sigurdson AS, Kampa D, Chimes K, Alexander BH, Ron E, Tarone RE, Linet MS (2003) Randomized trial of financial incentives and delivery methods for improving response to a mailed questionnaire. Am J Epidemiol 157:643–651

    Article  Google Scholar 

  • Dosemeci M, Rothman N, Yin SN, Li GL, Linet M, Wacholder S, Chow WH, Hayes RB (1997) Validation of benzene exposure assessment. Ann NY Acad Sci 837:114–121

    Article  Google Scholar 

  • DuChene AG, Hultgren DH, Neaton JD, Grambsch PV, Broste SK, Aus BM, Rasmussen WL (1986) Forms control and error detection procedures used at the Coordinating Center of the Multiple Risk Factor Intervention Trial (MRFIT). Control Clin Trials 7:34S–45S

    Article  Google Scholar 

  • Eaker S, Bergstrom R, Bergstrom A, Adami HO, Nyren O (1998) Response rate to mailed epidemiologic questionnaires: a population-based randomized trial of variations in design and mailing routines. Am J Epidemiol 147:74–82

    Google Scholar 

  • Easterbrook PJ, Berlin JA, Gopalan R, Matthews DR (1991) Publication bias in clinical research. Lancet 337:867–872

    Article  Google Scholar 

  • Edwards P, Roberts I, Clarke M, DiGuiseppi C, Pratap S, Wentz R, Kwan I (2002) Increasing response rates to postal questionnaires: systematic review. Br Med J 324:1183

    Article  Google Scholar 

  • Edwards S, Slattery ML, Mori M, Berry TD, Caan BJ, Palmer P, Potter JD (1994) Objective system for interviewer performance evaluation for use in epidemiologic studies. Am J Epidemiol 140:1020–1028

    Google Scholar 

  • Egger M, Smith GD (1998) Bias in location and selection of studies. Br Med J 316:61–66

    Google Scholar 

  • Feinstein AR, Cicchetti DV (1990) High agreement but low kappa: I. The problems of two paradoxes. J Clin Epidemiol 43:543–549

    Article  Google Scholar 

  • Fleiss JL (1981) Statistical methods for rates and proportions, 2nd edn. John Wiley and Sons, New York

    MATH  Google Scholar 

  • Fleming TR (1993) Data monitoring committees and capturing relevant information of high quality. Stat Med 12:565–570

    Article  Google Scholar 

  • Fowler F, Mangione T (1986) Reducing interviewer effects on health survey data. Center for Survey Research, University of Massachusetts, Boston, MA

    Google Scholar 

  • Fowler F, Mangione T (1990) Standardized survey interviewing: minimizing interviewer-related error. Sage Publications, Newberry Park, CA

    Google Scholar 

  • Freedland KE, Carney RM (1992) Data management and accountability in behavioral and biomedical research. Am Psychol 47:640–645

    Article  Google Scholar 

  • Gassman JJ, Owen WW, Kuntz TE, Martin JP, Amoroso WP (1995) Data quality assurance, monitoring, and reporting. Control Clin Trials 16:104S–136S

    Article  Google Scholar 

  • Gibson PJ, Koepsell TD, Diehr P, Hale C (1999) Increasing response rates for mailed surveys of Medicaid clients and other low-income populations. Am J Epidemiol 149:1057–1062

    Google Scholar 

  • Gilbart E, Kreiger N (1998) Improvement in cumulative response rates following implementation of a financial incentive. Am J Epidemiol 148:97–99

    Google Scholar 

  • Gilbert EH, Lowenstein SR, Koziol-McLain J, Barta DC, Steiner J (1996) Chart reviews in emergency medicine research: Where are the methods? Ann Emerg Med 27:305–308

    Article  Google Scholar 

  • Gissler M, Teperi J, Hemminki E, Merilainen J (1995) Data quality after restructuring a national medical registry. Scand J Soc Med 23:75–80

    Google Scholar 

  • Goldberg J, Gelfand HM, Levy PS (1980) Registry evaluation methods: a review and case study. Epidemiol Rev 2:210–220

    Google Scholar 

  • Goldman LR (2001) Epidemiology in the regulatory arena. Am J Epidemiol 154: S18–S26

    Article  Google Scholar 

  • Goodman SN (1999a) Toward evidence-based medical statistics. 2: The Bayes factor. Ann Intern Med 130:1005–1013

    Google Scholar 

  • Goodman SN (1999b) Toward evidence-based medical statistics: 1. The P value fallacy. Ann Intern Med 130:995–1004

    Google Scholar 

  • Gordis L (2000) Epidemiology, 2nd edn. W.B. Saunders, Philadelphia

    Google Scholar 

  • Greenbaum DS, Bachmann JD, Krewski D, Samet JM, White R, Wyzga RE (2001) Particulate air pollution standards and morbidity and mortality: case study. Am J Epidemiol 154:S78–S90

    Article  Google Scholar 

  • Halpern SD, Ubel PA, Berlin JA, Asch DA (2002) Randomized trial of 5 dollars versus 10 dollars monetary incentives, envelope size, and candy to increase physician response rates to mailed questionnaires. Med Care 40:834–839

    Article  Google Scholar 

  • Hawkins N, Evans J (1989) Subjective estimation of toluene exposures: a calibration study of industrial hygienists. Appl Ind Hygiene 4:61–68

    Google Scholar 

  • Hearst N, Hulley SB (1988) Using secondary data. In: Hulley SB, Cummings SR (eds) Designing clinical research. Williams & Wilkins, Baltimore, MD, pp. 53–62

    Google Scholar 

  • Heilbrun LK, Nomura A, Stemmermann GN (1991) The effects of non-response in a prospective study of cancer: 15-year follow-up. Int J Epidemiol 20:328–338

    Article  Google Scholar 

  • Hill J (2003) Certification in the Cardiovascular Health Study. Personal communication with Rajaraman P

    Google Scholar 

  • Hilner JE, McDonald A, Van Horn L, Bragg C, Caan B, Slattery ML, Birch R, Smoak CG, Wittes J (1992) Quality control of dietary data collection in the CARDIA study. Control Clin Trials 13:156–169

    Article  Google Scholar 

  • Hoffman SC, Burke AE, Helzlsouer KJ, Comstock GW (1998) Controlled trial of the effect of length, incentives, and follow-up techniques on response to a mailed questionnaire. Am J Epidemiol 148:1007–1011

    Google Scholar 

  • Holford TR, Stack C (1995) Study design for epidemiologic studies with measurement error. Stat Methods Med Res 4:339–358

    Google Scholar 

  • Horbar JD, Leahy KA (1995) An assessment of data quality in the Vermont-Oxford Trials Network database. Control Clin Trials 16:51–61

    Article  Google Scholar 

  • Hosking JD, Rochon J (1982) A comparison of techniques for detecting and preventing key-field errors. Proceedings of the Statistical Computing Section. 82–87. American Statistical Association, Washington, D.C.

    Google Scholar 

  • Hosking JD, Newhouse MM, Bagniewska A, Hawkins BS (1995) Data collection and transcription. Control Clin Trials 16:66S–103S

    Article  Google Scholar 

  • Hunt JR, White E (1998) Retaining and tracking cohort study members. Epidemiol Rev 20:57–70

    Google Scholar 

  • International Organization for Standardization (2003) ISO 9000:2000, ISO Technical Committee ISO/TC 176

    Google Scholar 

  • Ioannidis JP (1998) Effect of the statistical significance of results on the time to completion and publication of randomized efficacy trials. JAMA 279:281–286

    Article  Google Scholar 

  • James J, Bolstein R (1992) Large monetary incentives and their effect on mail survey response rates. Public Opinion Quarterly 56:442–453

    Article  Google Scholar 

  • John EM, Savitz DA (1994) Effect of a monetary incentive on response to a mail survey. Ann Epidemiol 4:231–235

    Article  Google Scholar 

  • Johnstone FD, Brown MC, Campbell D, MacGillivray I (1981) Measurement of variables: data quality control. Am J Clin Nutr 34:804–806

    Google Scholar 

  • Kaaks R, Ferrari P, Ciampi A, Plummer M, Riboli E (2002) Uses and limitations of statistical accounting for random error correlations, in the validation of dietary questionnaire assessments. Public Health Nutr 5:969–976

    Article  Google Scholar 

  • Kalantar JS, Talley NJ (1999) The effects of lottery incentive and length of questionnaire on health survey response rates: a randomized study. J Clin Epidemiol 52:1117–1122

    Article  Google Scholar 

  • Kannel WB (2000) Risk stratification in hypertension: new insights from the Framingham Study. Am J Hypertens 13:3S–10S

    Article  Google Scholar 

  • Kellerman SE, Herold J (2001) Physician response to surveys. A review of the literature. Am J Prev Med 20:61–67

    Article  Google Scholar 

  • Kessler RC, Little RJ, Groves RM (1995) Advances in strategies for minimizing and adjusting for survey nonresponse. Epidemiol Rev 17:192–204

    Google Scholar 

  • Kiesler S, Sproull L (1986) Response effects in the electronic survey. Public Opinion Quarterly 50:402–413

    Article  Google Scholar 

  • Kipen HM, Cody RP, Goldstein BD (1989) Use of longitudinal analysis of peripheral blood counts to validate historical reconstructions of benzene exposure. Environ Health Perspect 82:199–206

    Article  Google Scholar 

  • Kjelsberg MO, Cutler JA, Dolecek TA (1997) Brief description of the Multiple Risk Factor Intervention Trial. Am J Clin Nutr 65:191S–195S

    Google Scholar 

  • Knatterud GL, Rockhold FW, George SL, Barton FB, Davis CE, Fairweather WR, Honohan T, Mowery R, O’Neill R (1998) Guidelines for quality assurance in multicenter trials: a position paper. Control Clin Trials 19:477–493

    Article  Google Scholar 

  • Krewski D, Burnett RT, Goldberg MS, Hoover K, Siemiatycki J, Abrahamowicz M, White WH (2000) Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of particulate air pollution and mortality. Investigators’ reports parts I and II. Health Effects Institute, Cambridge, MA

    Google Scholar 

  • Kromhout H, Oostendorp Y, Heederik D, Boleij JS (1987) Agreement between qualitative exposure estimates and quantitative exposure measurements. Am J Ind Med 12:551–562

    Article  Google Scholar 

  • Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Article  MATH  MathSciNet  Google Scholar 

  • Ling PM, Glantz SA (2002) Using tobacco-industry marketing research to design more effective tobacco-control campaigns. JAMA 287:2983–2989

    Article  Google Scholar 

  • Little RE, Davis AK (1984) Effectiveness of various methods of contact and reimbursement on response rates of pregnant women to a mail questionnaire. Am J Epidemiol 120:161–163

    Google Scholar 

  • Maclure M, Schneeweiss S (2001) Causation of bias: the episcope. Epidemiol 12: 114–122

    Article  Google Scholar 

  • Maclure M, Willett WC (1987) Misinterpretation and misuse of the kappa statistic. Am J Epidemiol 126:161–169

    Google Scholar 

  • Maheux B, Legault C, Lambert J (1989) Increasing response rates in physicians’ mail surveys: an experimental study. Am J Public Health 79:638–639

    Google Scholar 

  • Martinson BC, Lazovich D, Lando HA, Perry CL, McGovern PG, Boyle RG (2000) Effectiveness of monetary incentives for recruiting adolescents to an intervention trial to reduce smoking. Prev Med 31:706–713

    Article  Google Scholar 

  • Maudsley G, Williams EM (1999) What lessons can be learned for cancer registration quality assurance from data users? Skin cancer as an example. Int J Epidemiol 28:809–815

    Article  Google Scholar 

  • McQuade CE, Kutvirt DM, Brylinski DA, Samet JM (1983) A tracking system for conducting epidemiological case-control studies. Comput Programs Biomed 16:149–153

    Article  Google Scholar 

  • Meinert CL, Tonascia S (1986) Controlled clinical trials: design, conduct, and analysis. Oxford University Press, New York

    Google Scholar 

  • Moorman PG, Newman B, Millikan RC, Tse CK, Sandler DP (1999) Participation rates in a case-control study: the impact of age, race, and race of interviewer. Ann Epidemiol 9:188–195

    Article  Google Scholar 

  • Mullooly JP (1990) The effects of data entry error: an analysis of partial verification. Comput Biomed Res 23:259–267

    Article  Google Scholar 

  • Neaton JD, DuChene AG, Svendsen KH, Wentworth D (1990) An examination of the efficiency of some quality assurance methods commonly employed in clinical trials. Stat Med 9:115–123

    Article  Google Scholar 

  • Olson SH (2001) Reported participation in case-control studies: changes over time. Am J Epidemiol 154:574–581

    Article  Google Scholar 

  • Olson SH, Voigt LF, Begg CB, Weiss NS (2002) Reporting participation in casecontrol studies. Epidemiol 13:123–126

    Article  Google Scholar 

  • Paolo AM, Bonaminio GA, Gibson C, Partridge T, Kallail K (2000) Response rate comparisons of e-mail-and mail-distributed student evaluations. Teach Learn Med 12:81–84

    Article  Google Scholar 

  • Parkes R, Kreiger N, James B, Johnson KC (2000) Effects on subject response of information brochures and small cash incentives in a mail-based case-control study. Ann Epidemiol 10:117–124

    Article  Google Scholar 

  • Perneger TV, Etter JF, Rougemont A (1993) Randomized trial of use of a monetary incentive and a reminder card to increase the response rate to a mailed health survey. Am J Epidemiol 138:714–722

    Google Scholar 

  • Post W, Kromhout H (1991) Semiquantitative estimates of exposure to methylene chloride adn styrene: the influence of quantitative exposure data. Applied Occupational and Environmental Hygiene 6:197–204

    Google Scholar 

  • Prud’homme GJ, Canner PL, Cutler JA (1989) Quality assurance and monitoring in the Hypertension Prevention Trial. Hypertension Prevention Trial Research Group. Control Clin Trials 10:84S–94S

    Article  Google Scholar 

  • Quan SF, Howard BV, Iber C, Kiley JP, Nieto FJ, O’Connor GT, Rapoport DM, Redline S, Robbins J, Samet JM, Wahl PW (1997) The Sleep Heart Health Study: design, rationale, and methods. Sleep 20:1077–1085

    Google Scholar 

  • Reisch LM, Fosse JS, Beverly K, Yu O, Barlow WE, Harris EL, Rolnick S, Barton MB, Geiger AM, Herrinton LJ, Greene SM, Fletcher SW, Elmore JG (2003) Training, quality assurance, and assessment of medical record abstraction in a multisite study. Am J Epidemiol 157:546–551

    Article  Google Scholar 

  • Rhodes SD, Bowie DA, Hergenrather KC (2003) Collecting behavioural data using the world wide web: considerations for researchers. J Epidemiol Community Health 57:68–73

    Article  Google Scholar 

  • Rosner B, Spiegelman D, Willett WC (1992) Correction of logistic regression relative risk estimates and confidence intervals for random within-person measurement error. Am J Epidemiol 136:1400–1413

    Google Scholar 

  • Rothman KJ, Greenland S (1998) Modern epidemiology, 2nd edn. Lippincott-Raven, Philadelphia

    Google Scholar 

  • Sacks FM, Handysides GH, Marais GE, Rosner B, Kass EH (1986) Effects of a low-fat diet on plasma lipoprotein levels. Arch Intern Med 146:1573–1577

    Article  Google Scholar 

  • Samet JM (2000) Epidemiology and policy: the pump handle meets the new millennium. Epidemiol Rev 22:145–154

    Google Scholar 

  • Samet JM, Lee NL (2001) Bridging the gap: perspectives on translating epidemiologic evidence into policy. Am J Epidemiol 154:S1–S3

    Article  Google Scholar 

  • Samet JM, Zeger SL, Kelsall JE, Xu J, Kalkstein LS (1997) Particulate air pollution and daily mortality: analyses of the effects of weather and multiple air pollutants (The Phase IB Report of the Particle Epidemiology Evaluation Project). Health Effects Institute, Cambridge, MA

    Google Scholar 

  • Schweitzer M, Asch DA (1995) Timing payments to subjects of mail surveys: cost-effectiveness and bias. J Clin Epidemiol 48:1325–1329

    Article  Google Scholar 

  • Shahar E, Folsom AR, Jackson R (1996) The effect of nonresponse on prevalence estimates for a referent population: insights from a population-based cohort study. Atherosclerosis Risk in Communities (ARIC) Study Investigators. Ann Epidemiol 6:498–506

    Article  Google Scholar 

  • Shaw MJ, Beebe TJ, Jensen HL, Adlis SA (2001) The use of monetary incentives in a community survey: impact on response rates, data quality, and cost. Health Serv Res 35:1339–1346

    Google Scholar 

  • Silver RC, Holman EA, McIntosh DN, Poulin M, Gil-Rivas V (2002) Nationwide longitudinal study of psychological responses to September 11. JAMA 288:1235–1244

    Article  Google Scholar 

  • Slattery ML, Edwards SL, Caan BJ, Kerber RA, Potter JD (1995) Response rates among control subjects in case-control studies. Ann Epidemiol 5:245–249

    Article  Google Scholar 

  • Sorensen HT, Sabroe S, Olsen J (1996) A framework for evaluation of secondary data sources for epidemiological research. Int J Epidemiol 25:435–442

    Article  Google Scholar 

  • Spiegelman D, Schneeweiss S, McDermott A (1997) Measurement error correction for logistic regression models with an “alloyed gold standard”. Am J Epidemiol 145:184–196

    Google Scholar 

  • Spry VM, Hovell MF, Sallis JG, Hofsteter CR, Elder JP, Molgaard CA (1989) Recruiting survey respondents to mailed surveys: controlled trials of incentives and prompts. Am J Epidemiol 130:166–172

    Google Scholar 

  • Steeh C (1981) Trends in nonresponse rates 1952–1979. Public Opinion Quarterly 45:40–57

    Article  Google Scholar 

  • Stram DO, Langholz B, Huberman M, Thomas DC (1999) Correcting for exposure measurement error in a reanalysis of lung cancer mortality for the Colorado Plateau uranium miners cohort. Health Phys 77:265–275

    Article  Google Scholar 

  • Szklo M, Nieto FJ (2000) Epidemiology: beyond the basics. Aspen, Gaithersburg, MD

    Google Scholar 

  • The Chemical Manufacturers Association’s Epidemiology Task Force (1991) Guidelines for good epidemiological practices for occupational and environmental epidemiologic research. J Occup Med 33:1221–1229

    Google Scholar 

  • Thompson WD (1990) Kappa and attenuation of the odds ratio. Epidemiol 1:357–369

    Article  Google Scholar 

  • Thompson WD, Walter SD (1988) A reaapraisal of the kappa coefficient. J Clin Epidemiol 41:949–958

    Article  Google Scholar 

  • Thornton A, Lee P (2000) Publication bias in meta-analysis: its causes and consequences. J Clin Epidemiol 53:207–216

    Article  Google Scholar 

  • Tielemans E, Heederik D, Burdorf A, Vermeulen R, Veulemans H, Kromhout H, Hartog K (1999) Assessment of occupational exposures in a general population: comparison of different methods. Occup Environ Med 56:145–151

    Google Scholar 

  • Turpin J, Rose R, Larsen B (2003) An adaptable, transportable web-based data acquisition platform for clinical and survey-based research. J Am Osteopath Assoc 103:182–186

    Google Scholar 

  • US Department of Health and Human Services (2001) Application of a Public Health Service Grant. PHS 398. Public Health Service

    Google Scholar 

  • US Department of Health Education and Welfare (DHEW) (1964) Smoking and health. Report of the Advisory Committee to the Surgeon General. DHEW Publication No. [PHS] 1103. U.S. Government Printing Office, Washington, DC

    Google Scholar 

  • US Department of Health Education and Welfare (DHEW) (1973) Final report of the Tuskegee Syphilis STudy Ad Hoc Advisory Panel. US Public Health Service, Washington, D.C.

    Google Scholar 

  • US Environmental Protection Agency (EPA) (1989) Toxic substances control act (TSCA): good laboratory practice standards. 40 CFR Part 792, 34034–34050

    Google Scholar 

  • Vantongelen K, Rotmensz N, van der Schueren E (1989) Quality control of validity of data collected in clinical trials. EORTC Study Group on Data Management (SGDM). Eur J Cancer Clin Oncol 25:1241–1247

    Article  Google Scholar 

  • Vardeman SB, Jobe JM (1999) Statistical quality assurance methods for engineers. John Wiley and Sons, Hoboken, N.J.

    Google Scholar 

  • Wacholder S, McLaughlin JK, Silverman DT, Mandel JS (1992) Selection of controls in case-control studies. I. Principles. Am J Epidemiol 135:1019–1028

    Google Scholar 

  • Wacholder S, Armstrong B, Hartge P (1993) Validation studies using an alloyed gold standard. Am J Epidemiol 137:1251–1258

    Google Scholar 

  • Wallace JM, Jr., Bachman JG, O’Malley PM, Johnston LD, Schulenberg JE, Cooper SM (2002) Tobacco, alcohol, and illicit drug use: racial and ethnic differences among U.S. high school seniors, 1976–2000. Public Health Rep 117Suppl 1:S67–S75

    Google Scholar 

  • White E, Hunt JR, Casso D (1998) Exposure measurement in cohort studies: the challenges of prospective data collection. Epidemiol Rev 20:43–56

    Google Scholar 

  • Whitney CW, Lind BK, Wahl PW (1998) Quality assurance and quality control in longitudinal studies. Epidemiol Rev 20:71–80

    Google Scholar 

  • Willett WC, Stampfer MJ, Underwood BA, Speizer FE, Rosner B, Hennekens CH (1983) Validation of a dietary questionnaire with plasma carotenoid and alpha-tocopherol levels. Am J Clin Nutr 38:631–639

    Google Scholar 

  • Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, Hennekens CH, Speizer FE (1985) Reproducibiltiy and validity of a semiquantitative food frequency questionaire. Am J Epidemiol 122:51–65

    Google Scholar 

  • Wright P, Haybittle J (1979a) Design of forms for clinical trials (1). Br Med J 2:529–530

    Article  Google Scholar 

  • Wright P, Haybittle J (1979b) Design of forms for clinical trials (2). Br Med J 2:590–592

    Google Scholar 

  • Wright P, Haybittle J (1979c) Design of forms for clinical trials (3). Br Med J 2:650–651

    Google Scholar 

  • Wyatt J (1995) Acquisition and use of clinical data for audit and research. J Eval Clin Pract 1:15–27

    Google Scholar 

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Authors and Affiliations

  1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard MSC 7242 Bethesda, Maryland, 20892-7335, USA

    Preetha Rajaraman

  2. Department of Epidemiology Bloomberg School of Public Health, The Johns Hopkins University, 615 N.Wolfe Street Suite W6041, Baltimore, MD, 21205, USA

    Jonathan M. Samet

Authors
  1. Preetha Rajaraman
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  2. Jonathan M. Samet
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Editors and Affiliations

  1. Division of Epidemiological Methods and Ethiologic Research, Bremen Institute for Prevention Research and Social Medicine (BIPS), Linzer Str. 10, 28359, Bremen, Germany

    Wolfgang Ahrens  & Iris Pigeot  & 

  2. Division of Biometrie and Data Management, Bremen Institute for Prevention Research and Social Medicine (BIPS), Linzer Str. 10, 28359, Bremen, Germany

    Wolfgang Ahrens  & Iris Pigeot  & 

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© 2005 Springer-Verlag Berlin Heidelberg

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Rajaraman, P., Samet, J.M. (2005). Quality Control and Good Epidemiological Practice. In: Ahrens, W., Pigeot, I. (eds) Handbook of Epidemiology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-26577-1_14

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