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研究法簡介

研究法簡介. 何明洲 中山醫學大學心理系. Single Factor – Two Levels. Single Factor – Two Levels. Independent groups design: use random assignment IV, manipulated Between-subject Matched groups design: use matching procedure IV, manipulated Between-subject. Single Factor – Two Levels.

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研究法簡介

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  1. 研究法簡介 何明洲 中山醫學大學心理系

  2. Single Factor – Two Levels

  3. Single Factor – Two Levels • Independent groups design: use random assignment • IV, manipulated • Between-subject • Matched groups design: use matching procedure • IV, manipulated • Between-subject

  4. Single Factor – Two Levels • Nonequivalent groups design • IV, subject • Still need to match participants • Between-subject • Repeated-measures design • IV, manipulated • Within-subject

  5. Analyzing single factor and two-level design • t test for independent groups and dependent groups

  6. EXAMPLE: THE t AND F TESTS • t value is a ratio of two aspects of the data, the difference between the group means and the variability within groups t = group difference within group variability

  7. Multilevel designs 如果只有2 levels (e.g., no reward and $4)， 資訊量太少， 可能誤判為linear Add more levels for replication and extension

  8. LINEAR VERSUS POSITIVE MONOTONIC FUNCTIONS

  9. 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?

  10. 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 …

  11. EXAMPLE: F TEST • Total variance = systematic variance + error variance • Systematic variance: deviation of group means from the grand mean  between-group variance • Grand mean: 全部皆平均, 假設無任何因IV所引發的差異 • Error variance: deviation of individual scores in each group from their respective group means  within-group variance

  12. EXAMPLE: F TEST Total variance = systematic variance + error variance • 變異的程度反應整個實驗情境和總人數所帶有的變異程度 • 實驗情境越多,總人數越多, 則變異程度大 • 不能只考慮變異程度, 須考慮平均每個實驗情境和人數, 所帶有的變異程度 F = (systematic variance/dfsystematic) / (error variance/dferror)

  13. Factorial Designs > 1 IVs

  14. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS • > 1 IVs • Factorial Designs 多因子設計: 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）

  15. Factorial matrix

  16. Factorial matrix

  17. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS • Simplest Factorial Design • 2 x 3x 4 (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…

  18. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: 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

  19. 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

  20. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Interaction  NS Main effect of 噪音  NS Main effect of 難度  * 7.5 7.5 10 5

  21. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Interaction * Two main effects  NS 7.5 7.5 7.5 7.5

  22. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS Interaction * Two main effects  * 15.5 27 13 29.5

  23. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS

  24. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS

  25. 2 x 3 x 4 factorial design • How many IVs? • How many levels of each IV • How many total conditions • How many DVs?

  26. Varieties of Factorial Design • Mixed factorial design: 有between and within subject variables, 沒有subject variable • P x E factorial designs: 有subject variable和manipulated variable（均為between) • Mixed P x E factorial :有subject variable和manipulated variable（有between 和 within)

  27. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS • Interactions and Simple Main Effects(單純主要效果) • 當有interaction時，必作的統計分析 • Simple main effect: examine mean differences at each level of the independent variable • 依研究目的決定要作哪些simple main effect

  28. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS • Interactions and Simple Main Effects • Simple main effect of B1: A1|B1 vs. A2|B1 • Simple main effect of A1: B1|A1 vs. B2|A1

  29. (Easy vs. Hard)|Low (L vs.M vs.H)|Easy

  30. INCREASING THE NUMBER OF VARIABLES: FACTORIAL DESIGNS

  31. INCREASING THE NUMBER OF INDEPENDENT VARIABLES: FACTORIAL DESIGNS • Increasing the Number of Independent Variables in a Factorial Design • 2 x 2 x 2 • 噪音高低 x 作業難易 x 性別

  32. 噪音高低 x 作業難易 x 性別 女 男 作業難易 作業難易 噪 音 高 低 噪 音 高 低 3-way interaction  2-way interaction (男生中，噪音高低 x 作業難易)  simple simple main effect

  33. Presenting data Text Table Figure

  34. Discrete and continuous variable

  35. Continuous variable

  36. 圖表 • 運用之法，存乎一心，沒有絕對對錯，重要的是「好理解」且「點出重點」

  37. 點出文章重點

  38. 圖表尺度的影響 • 注意尺度 • 加上信賴區間

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