1. 研究方法與實例簡介 中山醫學大學 心理系 何明洲 如要採用，請告知作者，並註明出處

2. 大綱 • 實驗設計簡介 • Within-subject design • Single factor • Multiple factors • Between-subject design • Mixed design • 論文實例介紹

3. 研究之初 • 研究問題的建立與改變 • 同一個研究問題細分成許多不同的研究方向來檢驗此問題 • 不同的研究方向延伸出其他的研究問題 • 匯集而成的研究成果，逐漸建立理論 • 再由理論延伸出相關問題

4. 實驗設計簡介

5. Within-Subject Design • Also called repeated-measures design • Experiment time is usually brief (< 30 minutes) • Good when the population of interest is scarce • 例如：betel nut chewer

6. Within-Subject Design • No need to worry about equivalent group problem • Statistically, remove the variance due to the individual difference from the nonsystematic error, increasing the probability to reject null hypothesis

7. SSbetween subj NO difference between treatments due to subject difference ∵ within-treatment errors include between-subject difference

8. Counterbalance Testing once per condition • Complete counterbalance • 2 conditions: 2!=2 orders (at least 2 participants), [1,2] [2,1] • 3 conditions : 3!=6 orders (at least 6 participants), [1,2,3] [1,3,2] [2,1,3] [2,3,1] [3,1,2] [3,2,1] • 4 conditions : 4!=24 orders (at least 24 participants) • 10 conditions : 10!=3628800 orders • GOOD for fewer conditions

9. Counterbalance

10. Counterbalance • Many conditions (e.g., > 3): Use partial counterbalancing • Latin squares：1.each condition appears once in each raw and column; 2. Each condition precedes and follows each condition one time

11. Block randomization • Block randomization：當每一種情境出現的次數超過一次時，可使用此法 • In each block，condition orders are randomized • 3 conditions (A, B, C)

12. Block 1 Block 2 C-B-A A-C-B Block 1 Block 2 A x 3 B x 3 C x 3 A x 3 B x 3 C x 3

13. Block randomization • 情緒刺激（雙字詞或臉）x情緒種類（中性、恐懼或高興）x 5 repetitions (trials) • 6 (2x3) conditions, each repeats 5 times • 共2 x 3 x 5 = 30 trials • 分兩個block進行，一個block有30 trials。故實驗共有60 trials (30 trials x 2 blocks)

14. Block 1 Block 2 A x 5 B x 5 C x 5 D x 5 E x 5 F x 5 A x 5 B x 5 C x 5 D x 5 E x 5 F x 5

15. Block randomization • 可和counterbalancing搭配 • 情緒刺激（雙字詞或臉）x 情緒種類（中性、恐懼或高興）x 5 repetitions (trials) • First block: 雙字詞（15 trials = 3 x 5） • Second block: 臉（15 trials = 3 x 5） • complete counterbalance [1,2] [2,1] • 看實驗結果來判斷是否和counterbalancing搭配

16. 臉 詞 Block 1 Block 2 A x 5 B x 5 C x 5 A x 5 B x 5 C x 5 詞 臉 Block 1 Block 2 A x 5 B x 5 C x 5 A x 5 B x 5 C x 5

17. Within-Subjects, Single factor

18. Within-Subjects, Single factor • 2 levels • Lee and Aronson (1974), how do we maintain balance in a moving environment • IV: moving direction of wall and ceiling (backward or forward) • Student’s t test • ≥ 2 levels • Steele, Ball, and Runk (1997), examine the Mozart effect • IV: Listening music (control, Mozart, and soothing environment sounds)

19. Analyzing Single-Factor, >2 levels • F Test (analysis of variance, ANOVA變異數分析) • ≥ 2 conditions (or groups) • When 2 conditions, F = t2 • When more than 2 conditions, why not use t test?

20. EXAMPLE: F Test • 用t test作多重比較, 至少出現一個type I error機率 • 1 – (1 – alpha)c (C: # of paired comparisons) • 噪音程度(無,低,中,高)對記憶的影響 • C = 4!/(2!2!) = 6 • 1-(1-.05)6 = .26 (=26%!!!) • F test 同時比較多組, alpha控制在.05 • H0: μ1 = μ2 = μ3 = μ4 …

21. EXAMPLE: F Test • Omnibus F test • H0: μ1 = μ2 = μ3 = μ4 … • Post hoc comparisons • Paired comparisons • Control “overall” alphaat .05 • Many control methods: Bonferroni, Shaffer, Sheffet and so on

22. Within-Subjects, multiple factors

23. FACTORIAL DESIGNS • Factorial Designs : Designs with more than one independent variable (or factor) • 噪音（高 vs.低）影響雙字詞記憶 • 噪音（高 vs.低） x 詞頻（高 vs.低）

24. Factorial matrix

25. Factorial matrix

26. FACTORIAL DESIGNS • Simplest Factorial Design • 2 x 2 (two-by-two) factorial design • Has two independent variables, each IV has 2 levels • 4 conditions • Number of levels of first IV x Number of levels of second IV x Number of levels of third IV…

27. FACTORIAL DESIGNS • Interpretation of Factorial Designs (A x B) • Main effects of an independent variable：effect of A factor ONLY (regardless of B factor, average out B factor) • Interaction between the independent variables (how does effect of A factor vary with B factor?)，條件機率 • A (A1, A2) x B (B1, B2) • 使用圖表讓讀者瞭解

29. A - B = C – D 詞頻的效果是否隨者噪音程度改變 A – C = B – D 噪音效果是否隨者詞頻程度改變

30. FACTORIAL DESIGNS

31. FACTORIAL DESIGNS • NOTE: Once you obtain both main and interaction effects, interpret the interaction in higher priority

32. 論文實例介紹

33. 常見名詞解釋 • SOA (Stimuli Onset Asynchrony) • ISI (Inter-Stimuli Interval) • Visual angle • Viewing distance • 視角  公分  畫素

34. SOA (stimulus onset asynchrony) ISI (inter-stimuli interval) On Off On Off S1 S2 Time

35. 論文通常都給viewing distance與visual angle，要自行轉成公分和畫素 Fig. 8-26, p. 181

36. 視角  公分

37. 公分視角

38. 公分  畫素 • dpi (dot per inch):每英吋所呈現的列印點數 • 右鍵內容設定值進階

39. 公分  畫素 • 螢幕解析度: 640x480 、 800x600 、 1024x768…等，解析度越來越好，因為螢幕單位長度中塞進了更多的像素 • 螢幕尺寸 • 基本上 17 in螢幕，Eprime調1280x1024，會成為約96dpi • 同一螢幕同一刺激， Eprime解析度調越小，呈現刺激越大 • 畫好後，記得用尺量，較為準確

40. 方法結構 • Participants • Apparatus • Stimuli*** • Design*** • Procedure***

41. Right hemispheric dominance in processing of unconsciousnegative emotion Sato and Aoki

43. 3 x 2 factorial design

45. Viewing distance = 57 cm 視角  公分  畫素

48. The Impact of Emotion onPerception Zeelenberg, Wagenmakers and Rotteveel

50. 3 x 3 factorial design