পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Latent Growth Curve Model (LGC)× | মিশ্র প্রভাব মডেল (Mixed Effects Model)× | |
|---|---|---|
| ক্ষেত্র | পরিসংখ্যান | পরিসংখ্যান |
| পরিবার≠ | Latent structure | Regression model |
| উদ্ভবের বছর≠ | 1990 | 1982 |
| প্রবর্তক≠ | Meredith & Tisak | Laird & Ware |
| ধরন≠ | Latent variable / longitudinal growth model | Mixed effects regression |
| মৌলিক উৎস≠ | Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗ | Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963–974. DOI ↗ |
| অপর নাম | latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli | LME, LMM, mixed model, random effects model |
| সম্পর্কিত≠ | 5 | 4 |
| সারসংক্ষেপ≠ | The latent growth curve model is a structural equation modelling approach introduced by Meredith and Tisak (1990) for analysing change over time. It treats each individual's starting point (intercept) and rate of change (slope) as latent variables, simultaneously estimating the average trajectory across the sample and the extent to which individuals differ in their own trajectories. | A mixed effects model (or linear mixed model) extends ordinary regression by including both fixed effects — population-level parameters shared by all observations — and random effects that capture subject-, group-, or cluster-level variability. It is the standard tool for repeated-measures, longitudinal, and multilevel data where observations within the same unit are correlated. |
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