INITIALLY, MANY RESEARCHERS ASSUMED THAT BECAUSE AGGREGATED DATA COULD BE MISLEADING AT THE INDIVIDUAL LEVEL, EVERY SUCH INTERPRETATION HAD TO BE INCORRECT. MORE RECENTLY, IT HAS BECOME EVIDENT THAT (1) AGGREGATE DATA COULD SUGGEST FINDINGS THAT EXIST AT THE INDIVIDUAL LEVEL; (2) THE ANALYSIS OF AGGREGATE DATA COULD BE OF INTEREST IN ITSELF; (3) COMPARISON OF DIFFERENT LEVELS OF AGGREGATION AND INDIVIDUAL-LEVEL DATA COULD PROVIDE INTERESTING FINDINGS; AND (4) IT REQUIRES A PARTICULAR BRAND OF REDUCTIONISM TO ATTRIBUTE SOME CHARACTERISTICS ASSOCIATED WITH GEOGRAPHICAL AND OTHER AGGREGATION UNITS TO INDIVIDUALS. THE TOPICS INCLUDE COMPARING TWO REGRESSION METHODS MOST OFTEN RECOMMENDED FOR ASSESSING GROUP EFFECTS IN NONEXPERIMENTAL DATA; FOCUSING ON THE NATURE OF INTERVENING MECHANISMS THAT MEDIATE THE EFFECT OF SOCIAL STRUCTURE ON INDIVIDUAL OUTCOMES; AND DISCUSSING ISSUES AND SUGGESTING GUIDELINES FOR RESEARCHERS WORKING WITH RATIO DATA. TWO OTHER ARTICLES REVIEW PROBLEMS WITH ANALYSIS PROCEDURE AND INFERENCES WHEN RATIOS ARE COMPUTED BY USING THE SAME OR HIGHLY CORRELATED DENOMINATORS AND CLARIFY THE RELATIONSHIP BETWEEN TWO ALTERNATIVE WAYS OF ANALYZING A COMMON DATA STRUCTURE. ADDITIONAL CHAPTERS ENCOMPASS AGGREGATION BIAS, HOUSEHOLD MIGRATION PLANS (A MULTIVARIATE PROBIT MODEL), FACTORIAL ECOLOGY, AND THE DETERMINATION OF CRITICAL HEALTH PROBLEM AREAS. TABULAR DATA AND REFERENCES ARE PROVIDED FOR EACH CHAPTER. (AUTHOR ABSTRACT MODIFIED)