পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ক্রস-সেকশনাল এক্স পোস্ট ফ্যাক্টো ডিজাইন× | এক্স পোস্ট ফ্যাক্টো ডিজাইন× | |
|---|---|---|
| ক্ষেত্র | গবেষণা নকশা | গবেষণা নকশা |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1964–1973 | 1960s (systematic codification); concept used in social science from early 20th century |
| প্রবর্তক≠ | Fred N. Kerlinger (formalized ex post facto methodology) | Formalized by Fred N. Kerlinger; foundational treatment by Donald T. Campbell and Julian C. Stanley |
| ধরন | Non-experimental quantitative research design | Non-experimental quantitative research design |
| মৌলিক উৎস≠ | Kerlinger, F. N. (1973). Foundations of Behavioral Research (2nd ed.). Holt, Rinehart and Winston. ISBN: 978-0030862731 | Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. link ↗ |
| অপর নাম | cross-sectional causal-comparative design, retrospective cross-sectional design, after-the-fact cross-sectional study, cross-sectional EPF design | after-the-fact research, retrospective non-experimental design, causal-comparative design, EPF design |
| সম্পর্কিত≠ | 4 | 3 |
| সারসংক্ষেপ≠ | A cross-sectional ex post facto design investigates presumed causal relationships by comparing groups that already differ on a key characteristic — all measured at a single point in time. Because the independent variable (e.g., smoking history, prior educational attainment) has already occurred and cannot be manipulated, the researcher works backward from observed outcomes to infer probable antecedents. It is widely used in education, public health, and the social sciences when experimental control is ethically or practically impossible. | Ex post facto design is a non-experimental quantitative research approach in which the researcher investigates a phenomenon after it has already occurred, examining pre-existing differences between groups to explore potential causal or associative relationships. Because the independent variable cannot be manipulated — it happened in the past — the design relies on careful group selection, retrospective data collection, and statistical controls to approximate causal inference without experimental intervention. |
| ScholarGateডেটাসেট ↗ |
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