Bandingkan kaedah

	Penyelidikan Trend Berasaskan Panel	Kajian Kohort	ANOVA ukuran berulang
Bidang	Reka Bentuk Penyelidikan	Epidemiologi	Statistik
Keluarga	Process / pipeline	Process / pipeline	Hypothesis test
Tahun asal	1940s–1960s	Mid-20th century (formal epidemiological design codified ~1950s)	1992
Pengasas	Established through survey methodology and panel econometrics; foundational contributions by Paul Lazarsfeld (1940s) and later systematized by econometricians including Zvi Griliches and Yair Mundlak	Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854)	Girden (textbook treatment); Field (2013)
Jenis	Quantitative longitudinal observational design	Observational longitudinal study design	Parametric within-subjects mean comparison
Sumber perintis	Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922452	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
Alias	panel trend study, longitudinal panel design, repeated-measures panel survey, panel survey trend analysis	longitudinal study, follow-up study, panel study, incidence study	within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
Berkaitan	3	6	4
Ringkasan	Panel-based trend research tracks the same group of respondents — the panel — across multiple measurement waves over time, enabling researchers to separate genuine individual-level change from cohort differences and to model how variables evolve within persons. Unlike repeated cross-sectional designs, which sample new participants at each wave, a panel design retains the same units, giving it the power to detect within-person trajectories and causal ordering among variables.	A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome.	Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).