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Wingo, Phyllis A.; Howard W. Ory, Peter M. Layde, Nancy C. Lee, and the Cancer and Steroid Hormone Study Group. The evaluation of the data collection process for a multicenter, populationbased, case-control design. Am J Epidemiol 1988; 128:206-217. Plus several articles and comments in J Chron Dis 1985; 38(7) and responses in 1986; 39(7):565-571. Intervention trials: Chalmers, Thomas C.; Paul Celano, Henry S. Sacks, Harry Smith, Jr. Bias in treatment assignment in controlled clinical trials. N Engl J Med 1983; 309:1358-61. Farquhar, John W.; Stephen P. Fortmann, June A. Flora et al. Effects of communitywide education on cardiovascular disease risk factors: The Stanford Five-City Project. JAMA 1990;264:359-365. Feinstein, A.R. Clinical Epidemiology: The Architecture of Clinical Research. Chapter 29, pp. 683-718. Feinstein, Alvan R. Current problems and future challenges in randomized clinical trials. Circulation 1984; 70:767-774. Friedman L.M., Furberg, C.D., DeMets, D.L. Fundamentals of clinical trials. Boston: John Wright PSG Inc., 1982. Koepsell TD et al. Symposium on community trials: Invited commentary, 594-599 plus articles by Allan Donner, Stephen Fortmann, Sylvan Green. Am J Epidemiol 1995;142(6) Lavori, Philip W.; Thomas A. Louis, John C. Bailar III, Marcia Polansky. Designs for experiments– parallel comparisons of treatments. N Engl J Med 1983; 309:1291-8. Lilienfeld, Abraham M. Ceteris Paribus: The evolution of the clinical trial. Bulletin of the History of Medicine 56:1-18, 1982. Luepker R, et al. Community education for cardiovascular disease prevention: Risk factor change in the Minnesota Heart Health Program. Am J Public Health 1994;84:1383-1393. MacMahon and Pugh - Epidemiology: principles and methods, Chapter 13; Mausner and Kramer - Epidemiology: an introductory text, Chapter 8; Lilienfeld and Lilienfeld - Fundamentals of epidemiology, Chapters 10-11. Moses, Lincoln E. The series of consecutive cases as a device for assessing outcomes of intervention. N Engl J Med 1984; 311:705-710 Peto, R., Pike, M.C., Armitage, P. et al. Design and analysis of randomized clinial trials requiring prolonged observation of each patient. I. Introduction and design. Br J Cancer 34:585-612, 1976. _____________________________________________________________________________________________ www.sph.unc.edu/courses/EPID168, © Victor J. Schoenbach 1999 8. Analytic study designs - 250 rev. 9/6/1999, 10/7/1999, 12/17/1999
Peto, R., Pike, M.C., Armitage, P., et al. Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. Analysis and examples. Br J Cancer 35:1-39, 1977. Sacks, H., Chalmers, T.C., Smith, H. Randomized versus historical controls for clinical trials. Amer J Med 72:233-239, 1982. Schwartz, D., Lellouch, J. Explanatory and pragmatic attitudes in therapeutic trials. J Chron Dis 20:637-648, 1967. Simon, Richard and Robert E. Wittes. Methodologic guidelines for reports of clinical trials. Editorial. Cancer Treatment Reports 1985; 69:1-3. Weinstein, Milton C. Allocation of subjects in medical experiments. N Engl J Med 291:1278-1285, 1974. _____________________________________________________________________________________________ www.sph.unc.edu/courses/EPID168, © Victor J. Schoenbach 1999 8. Analytic study designs - 251 rev. 9/6/1999, 10/7/1999, 12/17/1999
Page 1 and 2:
Understanding the Fundamentals of E
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Preface Introductory epidemiology c
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Table of Contents Chapter (in Acrob
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1. Introduction Definition, charact
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problems (Schwartz and Carpenter, 1
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HIV - a new or newly-recognized vir
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d = principal investigator's degree
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Analytic studies typically involve
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Observational sciences especially a
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McGavran EG. What is public health?
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2. An evolving historical perspecti
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Time line for the history of public
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as a one-room bacteriology laborato
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− Health surveys − Research fun
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his scientific peers of the correct
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Kuhn, Thomas S. The structure of sc
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3. Studying populations - basic dem
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The demographic balancing equation
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ates. Similarly, bulges in the repr
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When the baby boom cohort retires 1
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The pervasiveness, strength, viciou
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Total fertility rate (TFR) Standard
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Life expectancy The technique, of u
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Excerpt from the U.S. 1993 abridged
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At the other end of the life table,
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to change, hopefully to decline. If
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Thought question: Professors typica
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Descriptive studies and surveillanc
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4. The Phenomenon of Disease Concep
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Classification is the foundation As
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As we gain more sophisticated under
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To recapitulate the above discussio
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Classifying cause of death Since mo
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Laboratory and other objectively me
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distribution but are not diabetic (
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program in the general population,
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Infectious disease Incubation "time
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the direct effects of carcinogenic
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patient outcomes. The design and ev
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detected by screening will appear b
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Morrison, Alan S. Screening in chro
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e relevant. Compromises might be fo
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educational attainment by the numbe
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Distributions - the fuller picture
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Per capita income: Should health ca
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Deaths of children < 1 year of age
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No. of persons with senile dementia
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Incidence Immigration Relationship
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Examples: arthritis, cholelithiasis
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Cohort - entrance into the populati
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Sample calculation: 200 people free
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• The units of time must be state
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Calculation of person-time in a coh
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Original Calculation of person-time
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average risk for a member of the co
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However: Nurses: 601 cases/89,538 w
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treated. If the rate at which patie
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Incidence and prevalence in a popul
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small prevalence. So if the seropre
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Appendix on weighted averages Becau
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Appendix on exponents and logarithm
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and epidemiology. The notation ln(x
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3. For the following hypothetical d
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c. ________________ 6 fatalities /
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Measuring disease and exposure - As
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5. a. Flow Diagram Population of si
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New cases Q ID = ------------------
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Overview 6. Standardization of rate
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differences between the groups in f
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∑ (stratum-specific rates × stan
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especially important when comparing
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copy this cell to the other columns
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where the RR k are the stratum-spec
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and the observed number of deaths i
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Directly standardized rate for A =
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5,022 Indirectly standardized = —
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the situation among older age group
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Appendix on Standardized Mortality
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across age strata, then the damage
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d. How would you feel about the con
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Cases per 100,000 Mean annual incid
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d. dt Indirectly standardized rates
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The second ingredient for an standa
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Group US rate /100,000 County pop.
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Crude rates are comparable because
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The “Big Picture” 7. Relating r
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CHD and oral contraceptives in Brea
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Some basic measures Before diving i
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esophageal cancer? First, if we did
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ought in here as well. When we cont
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Exposure Disease Yes No Total Yes a
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Relation of the odds ratio to the r
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the case-control study estimates th
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If the data had come from a cross-s
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Excess risk = CIR - 1 = 1.0 (i.e.,
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strength of the relationship (e.g.,
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drawn on ordinary graph paper. Howe
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Measures of Impact Concept Relative
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Attributable risk proportion The AR
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show that a large proportion (i.e.,
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Incidence Diagrammatic representati
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1. high frequency of disease 2. pow
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With this diagram and notation we c
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vaguer) “attributed to”. Incide
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Summary There are three categories
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CIR can be directly estimated if th
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I0 I = ——————— 1 + P1
Page 215 and 216: PD|e PE (RR - 1) PD|e PE (RR - 1) P
Page 217 and 218: Walter, Stephen D. Choice of effect
Page 219 and 220: a. Quit rates were measured as the
Page 221 and 222: 1. Definitions: Relating risk facto
Page 223 and 224: There is an extremely strong associ
Page 225 and 226: 8. Analytic study designs The archi
Page 227 and 228: Progression of types of studies In
Page 229 and 230: Cross-sectional A cross-sectional s
Page 231 and 232: Follow-up studies Along with case-c
Page 233 and 234: of interest community-level influen
Page 235 and 236: ecological approach may be the appr
Page 237 and 238: What measures can be estimated from
Page 239 and 240: Ability to estimate risk Ascertainm
Page 241 and 242: individuals, this relationship does
Page 243 and 244: Odds Ratio (OR) Exposure odds in ca
Page 245 and 246: Simple randomization - assignment o
Page 247 and 248: The relationship of an attribute to
Page 249 and 250: (a / m1) / (b / m1) ad ORe (Exposur
Page 251 and 252: Validity The validity of a case-con
Page 253 and 254: Since the strategic advantage of th
Page 255 and 256: c = f0N1 = number of exposed noncas
Page 257 and 258: experienced the event under study.
Page 259 and 260: approach, the odds ratio computatio
Page 261 and 262: Exposure Yes No Total Cases A B M1
Page 263 and 264: Miettinen, Olli S. The clinical tri
Page 265: Mantel, N. and Haenszel, W.: Statis
Page 269 and 270: 4. The authors state that "There we
Page 271 and 272: 5. In contrast to many earlier inve
Page 273 and 274: In this study the use of hospitaliz
Page 275 and 276: Follow-up must be longer for any gi
Page 277 and 278: While acknowledging the very import
Page 279 and 280: world. Even as late as the 1950's,
Page 281 and 282: Causal Inference Direct observation
Page 283 and 284: data on the effects of radiation on
Page 285 and 286: But excluding an explanation based
Page 287 and 288: Strength of the association Pronou
Page 289 and 290: Experimental evidence Certain types
Page 291 and 292: To issue an indictment, the grand j
Page 293 and 294: 10. Sources of error A systematic f
Page 295 and 296: the data in the table. (Note that t
Page 297 and 298: associations. So the same terms may
Page 299 and 300: "Negative bias" - The observed meas
Page 301 and 302: Classifying sources of bias Inspite
Page 303 and 304: The study population is a subset of
Page 305 and 306: This estimate of the prevalence of
Page 307 and 308: unmatched control groups will presu
Page 309 and 310: The odds ratio for this table is 3.
Page 311 and 312: Selection bias in cohort studies Se
Page 313 and 314: Information bias Information bias r
Page 315 and 316: following chapter). The concept of
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P h y s i c i a n A Comparison of d
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item). Alpha values of 0.80 are are
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Hypothetical scenario showing effec
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presumably classified as informatio
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Appendix 1 Formulas to see the effe
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Algebraically, _ Pr(E|D') = — the
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Gregorio, David L.; James R. Marsha
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Sources of error - Assignment 1. Th
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Alpha (α) is the probability by wh
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Sources of error - Assignment solut
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3. ii) Selective survival--if OC us
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a. Flow diagram: 1960-1962 1967-196
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Introduction 11. Multicausality: Co
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estimate of what the outcomes would
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A hypothetical example (with apolog
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Questions to ask: There are many as
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Confounding arises from unequal dis
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CHD Incidence by Behavior Pattern a
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In this way, the 1,129 Type A's wit
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exposure. If we assume a baseline r
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Further insight can be gained by co
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Table 7a Colon cancer and drinking
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atio of the observed number of expo
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ural-specific exposure prevalences,
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eing infected, and the more of them
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studies deal with a delimited geogr
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University of Massachusetts at Amhe
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similarly distributed in cases and
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"There have been many important ste
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MAIN POINTS Confounding is a disto
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Greenland, S. and Neutra R.: Contro
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Appendix The following discussion i
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i n1i wi = ----- If exposure is unr
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Multicausality: Confounding - Assig
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4. The following table, published i
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1. Multicausality: Confounding - As
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link between HCS and MI to ensure t
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Multicausality 12. Multicausality:
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Interdependent effects The precedin
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epidemiologic data. Put simply, the
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BP 0 These two lines are parallel;
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ean intake and B representing genet
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Fourth, proportion of disease attri
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Incidence and incidence ratios of f
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% with evidence of impaired red blo
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cancer rate among the light smokers
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Age standardized lung cancer rates
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R11 - R00 = R10 - R00 + R01 - R00 (
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and R111 = R100 × R010 × R001 / (
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R110 = R100 × R010 / R000 (multipl
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Risk ln(risk) 0.19 -1.67 0.13 -2.01
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have clinical or public health sign
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Baseline Characteristics Associated
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Weiss, Noel S. Accounting for the m
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A. Synergism apparently exists in t
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5. Walker (International Journal of
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(or equivalently, the rate for pers
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impact. Synergism in this sense imp
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13. Multicausality - analysis appro
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very far on instruments but needs t
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Summarizing the relationships Often
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We saw in the chapter on effect mod
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So the multiplicative model for joi
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misleading summary. These circumsta
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w1 CID1 + w2 CID2 Summary CID = —
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c d bcn0 + adn1 Var(ln(CIR)) ≈
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Kleinbaum, Kupper, and Morgenstern;
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1 + 1 + 1 3 ORMH = —————
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Risk = R00 + Obesity effect Obesity
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two (or more) factors that "interac
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OR = exp(β3) β3 is the difference
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Other regression models [Optional f
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Know the epidemiologic meaning of t
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14. Data analysis and interpretatio
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and questionable data. Monitoring p
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presence of particular proteins (e.
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4. Count - the number of entities,
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Algorithms - A procedure that uses
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Imputation causes the least distort
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Prenatal exposure to diethylstilbes
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Possible outcomes (Colors of pairs
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In a strict decision-making mode, t
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C = area between -z and +z D = area
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two-tailed 5% significance level).
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If the p-value is not small (i.e.,
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OR we observed was greater than 1.0
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Large trials (e.g., 250 deaths) Tru
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The concept behind the confidence i
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Formulas for confidence intervals f
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Woolf SH, Battista RN, Anderson GM,
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Stallones, Reuel A. The use and abu
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C - Clustered observations, which d
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For example, suppose that n, the sa
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* See previous table Margin of erro
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Even in randomized trials problems
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Pr(H|T) is therefore a function of
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That information gives you pause. C
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Part II 1. In table 2 from the Rose
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If the OR for Current OC use were t
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6. There are no interaction (produc
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24. Submit manuscript from previous
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Cooperative agreement A cooperative
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Assurances by the applicant and her
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The new element is the grant award.
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1. What needs to be done? 2. How lo
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Postaward Final report What to do
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2. maintain close supervision of th
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Publication Epidemiology Working Gr
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Weed, Douglas L. Between science an
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1.3 Specific Objectives of Data Man
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engender a basic conflict between t
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1.4.2 Integration Integrate the dat
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2. Consistency of the protocol's im
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2. Coding of a sample of data forms
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2.3 The steps in the Editing proces
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Although it is rare to use more tha
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The first stages of data analysis s
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have less power to exclude the stat
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greater nonresponse by heavy drinke
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Imputation is then carried out as f
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(normal) distribution in the popula
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Appendix **************************
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___________________________________
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Public health approach The public h
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health, particularly at the world l
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Causative or preventive agents Scur
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Human behavior is also biology The
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crowded, under-resourced urbanized
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Bibliography Annas, George J.; Leon
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18. Overview and Conclusion A look
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Epidemiology is expanding In recen
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More reliance on "soft money" - res
Page 581 and 582:
__________ This is not a new challe
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