Comparer des méthodes

	Recherche comparative par enquête	Recherche Descriptive
Domaine	Conception de la recherche	Conception de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	Mid-20th century onward	Late 19th century; formalized in social/behavioral sciences ~1960s–1980s
Auteur d'origine	Rooted in survey methodology traditions (Gallup, Likert, Lazarsfeld mid-20th century); comparative extension codified in social science research methods literature	Francis Galton, Karl Pearson (early empirical tradition); formalized in social science by Fred Kerlinger
Type	Quantitative non-experimental research design	Non-experimental quantitative research design
Source fondatrice	Fowler, F. J. (2014). Survey Research Methods (5th ed.). Sage Publications. ISBN: 978-1452259000	Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Sage. ISBN: 978-1452226101
Alias	comparative survey design, cross-group survey, multi-group survey research, comparative questionnaire study	descriptive study, descriptive survey design, observational descriptive research, non-experimental descriptive research
Apparentées	4	3
Résumé	Comparative survey research is a quantitative non-experimental design that systematically collects structured survey data from two or more clearly defined groups, populations, or contexts in order to identify, describe, and analyze similarities and differences among them. It extends basic survey research by making comparison the explicit organizing logic: rather than characterizing a single population, the goal is to detect how attitudes, behaviors, or outcomes vary across groups defined by nationality, culture, profession, demographic category, or time period.	Descriptive research is a non-experimental quantitative design that systematically documents the characteristics, frequencies, or distributions of variables in a defined population at a given point in time. It answers 'what is' questions — who, what, when, where, and how much — without manipulating variables or drawing causal conclusions. It is one of the most widely used research designs across the social, behavioral, health, and education sciences.