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A course for staff of the Global Center for Mass Medicine at the Ministry of Health by Dr. Omar Hasan Kasule MB ChB (MUK), MPH (Harvard), DrPH (Harvard) Professor of Epidemiology at King Fahad Medical City Riyadh
3.1 MEASURES OF ASSOCIATION and EFFECT
3.1.1 Tests of association for continuous data are the t-test, the F-test, the correlation coefficient, and the regression coefficient. The t-test is used for two sample means. Analysis of variance, ANOVA (F test) is used for more than 2 sample means.
3.1.2 The common test of association for discrete data is the chi-square test. The chi-square test is used to test the association of 2 or more proportions in contingency tables. The exact test is used to test proportions for small sample sizes.
3.1.3 Measures of Effect: The Mantel-Haenszel Odds Ratio is used for 2 proportions in a single or stratified 2x2 contingency table. Logistic regression can be used as an alternative to the MH procedure.
3.1.4 Validity and Precision: Validity is a measure of accuracy. Precision measures variation in the estimate. Internal validity is concerned with the results of each individual study. External validity is the generalizability of results.
3.1.5 Meta-Analysis: Meta-analysis refers to methods used to combine data from more than one study to produce a quantitative summary statistic.
3.2 SOURCES AND TREATMENT OF BIAS
3.2.1 Misclassification Bias: is an inaccurate assignment of exposure or disease status. Random is less dangerous than non-random.
3.2.2 Selection Bias: arises when subjects included in the study differ in a systematic way from those not included. It is due to biological factors, disease ascertainment procedures, or data collection procedures
3.2.3 Confounding Bias: Confounding is mixing up of effects. Confounding bias arises when the disease-exposure relationship is disturbed by an extraneous factor called the confounding variable.
3.2.4 Mis-Specification Bias: This type of bias arises when a wrong statistical model is used.
3.2.5 Survey Error: Total survey error is the sum of the sampling error and three non-sampling errors (measurement error, non-response error, and coverage error).
3.2.6 Sampling bias: The sources of bias are: incomplete or inappropriate sampling frame, use of a wrong sampling unit, non-response bias, measurement bias, coverage bias, and sampling bias.
3.3 HEALTH STATUS INFORMATION
3.3.1 Hospital Information Systems
3.3.2 Public Health Information System
3.3.3 Disease Registries with Cancer as an Example
3.3.4 Vital Health Statistics Interpretation (births): Crude Birth Rate (CBR) is births per 100,000 of mid-year population per year.
3.3.5 Vital Health Statistics Interpretation (deaths): Crude Death Rate (CDR) is deaths in a year per 100,000 of mid-year population. Proportional Mortality Ratio (PMR) is deaths of a specified kind as a proportion of the total number of deaths.
3.3.6 Vital Health Statistics Interpretation (deaths): Case-fatality ratio is the proportion of deaths from persons with a specified disease condition. The Infant Mortality Rate (IMR), the most important indicator of community health, is deaths at ages 0-12 months per 1000 live births per year.
3.3.7 Demographic Analysis: Total Fertility Rate (TFR) is births per year 1000 women aged 15-44 in the mid-year population. Population pyramid. Life expectancy at birth. Years of potential life lost.