เปรียบเทียบวิธี

	การวิจัยเชิงพรรณนาแบบลำดับชั้น	การวิจัยเชิงพรรณนาเปรียบเทียบ
สาขาวิชา	การออกแบบการวิจัย	การออกแบบการวิจัย
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1980s–1990s (multilevel descriptive formalization)	Mid-20th century, formalized in research methods texts from the 1960s onward
ผู้ริเริ่ม	Formalized within survey and educational research traditions; associated with Hox, Raudenbush, Bryk, and Creswell	Codified in educational and behavioral research methods literature; no single originator
ประเภท	Quantitative observational/descriptive design	Non-experimental quantitative research design
แหล่งต้นตำรับ	Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728455	Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to Design and Evaluate Research in Education (8th ed.). McGraw-Hill. ISBN: 978-0078097874
ชื่อเรียกอื่น	multilevel descriptive design, nested descriptive study, hierarchical survey design, stratified descriptive research	comparative survey design, descriptive comparative study, group-comparison descriptive research, CDR
ที่เกี่ยวข้อง	4	3
สรุป	Hierarchical descriptive research is an observational design that documents the current state of a phenomenon across two or more nested levels — for example, students within classrooms within schools, or employees within teams within organizations. Rather than testing hypotheses or explaining causation, it describes distributions, frequencies, and relationships at each level, making explicit the structured, layered nature of the population being studied.	Comparative descriptive research is a non-experimental quantitative design that systematically documents characteristics, attitudes, behaviors, or conditions across two or more naturally occurring groups, then places those descriptions side by side to identify similarities and differences. Unlike causal-comparative designs, it makes no claim about why groups differ — it rigorously answers the question 'How do these groups compare on this characteristic?' without manipulating any variable.