השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מבנה ניסויי אקראי מבוקר וכפול-סמיות× | תכנון ניסויי עם קבוצת ביקורת× | |
|---|---|---|
| תחום | תכנון ניסויים | תכנון ניסויים |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1930s–1950s (formalized in clinical trial methodology) | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| הוגה השיטה≠ | R. A. Fisher (experimental control foundations); blinding practices evolved in clinical research through the 20th century | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| סוג | Experimental research design | Experimental research design |
| מקור מכונן≠ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| כינויים | double-blind controlled experiment, DB-CG design, double-masked controlled trial, double-blind controlled study | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| קשורות≠ | 5 | 4 |
| תקציר≠ | A double-blind control group experimental design is a rigorous experimental structure in which participants are randomly assigned to at least one treatment group and one control group, while both the participants and the researchers collecting or assessing outcomes are kept unaware of group assignment. By combining allocation concealment with blinding at two levels, the design minimizes expectancy bias, placebo effects, and assessor bias simultaneously, making it a cornerstone of high-quality intervention research in medicine, psychology, and the social sciences. | Control group experimental design is a fundamental experimental structure in which participants are assigned to at least two groups — a treatment group that receives the intervention and a control group that does not — so that the effect of the intervention can be isolated by comparing outcomes across groups. Randomisation of assignment strengthens causal inference by balancing known and unknown confounders. |
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