6. What kind of mixed methods research is
PAC Analysis?
PAC分析はどのような種類の混合研究法か？
Takehiko Ito いとうたけひこ
Wako University, Tokyo 和光大学（東京）
0-17 （Proceedings page 69.）
www.itotakehiko.com www.pacanalysis.com
Mixed Methods International Research Association (MMIRA) Asia Regional
Conference 2017/ 3rd Japan Society for Mixed Methods Research (JSMMR)
Conference 2017
Ritsumeikan University
August 6, 2017
(国際混合研究法学会アジア地域会議／第3回日本混合研究法学会年次大会
2017年8月6日）
6
9. Purpose
• Personal Attitude Construct (PAC)
Analysis was proposed by Tetsuo Naito
(1993, 1997) as a method to seek for
the individual structure of attitude. 個
人別態度構造分析（内藤）
• The purpose of the present research is
to recharacterize PAC Analysis from the
perspective of mixed methods research
under the Methods-Strand Matrix
paradigm方法＊ストランド行列表
proposed by Teddlie and Tashakkori
(2009).
9
10. What is PAC Analysis?
• Personal Attitude Construct
(PAC) Analysis個人別態度構造
分析 was proposed by Tetsuo
Naito (1993, 1997) 内藤哲雄
• as a method to seek the
individual structure of attitude
（Case study）事例研究法
• using visualization
(dendrogram：QUAN data)樹形
図による量的データの可視化
and a dialogical interview
（Narrative: QUAL data）. 対話
的面接（語り：質的データ
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11. Two unique research methods originated in Japan
often referred as qualitative research methods
(QUAL) using diagrams(QUAN/QUAL)
日本発信の図を用いた２つの質的研究法
• PAC Analysis
(個人別態度行動分析)
• Trajectory Equfinality Approach
（複線径路等至性モデル）
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12. Characteristics of PAC Analysis
• Case study/single subject事例研究・１被験者
• QUAL > quan 質中心
• Sequential: QUAN -> QUAL 順次的: ->
• Successive: 継続的:
• Data conversion データ変換 QUAN -> QUAL
12
14. Phase ① QUAL （open-ended questions）
Procedure: By stimulus sentence (n=1),刺激文
Word association produced 連想法
Product: List of associated word/sentence連想項目
14
15. Phase ② quan (closed-ended questions)
Procedure: Paired-words rating of distance
一対比較法
Product: Distance Matrix距離行列
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16. Phase ③ quan (multivariate analysis)多変量解析
Procedure: Cluster Analysis クラスター分析
Product: Dendrogram 樹形図
16
17. Phase ④ quan → QUAL (open-ended questions)
Procedure: Ask the meaning of each and higher clusters
Product: Dialogue narrative & cluster name (=meaning)
面接でのナラティブ生成によるクラスターの意味化と命名
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18. Phase ⑤: Interpretation(open-ended questions)
Procedure: Cooperative dialogue to final interpretation
Product: cluster name (=meaning) &
fully explained dendrogram
高次クラスターの命名・意味化と全体の説明
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21. Three Hypotheses: PAC Analysis can
be characterized as either
• Hypothesis (1):multiplied mixed methods
research 乗算的ミックス法？ （Inoue & Ito, 2011）
or
• Hypothesis (2): explanatory sequential design
説明的順次デザイン？ (Ito, et al., 2015)
or
• Hypothesis (3): （monostrand） conversion
design （単線型）変換型デザイン？ （Teddlie &
Tashakkori, 2009）
21
22. (1)Characterizing PAC Analysis as
multiplied mixed methods research
(乗算的ミックス法) （Inoue & Ito,2011）
• Inoue and Ito (2011) argued that the PAC
Analysis is one of multiplied mixed
methods(乗算的ミックス法),
• while the mixed methods research is usually
referred to NOT multiplicative
（QUAL＊QUAN：かけ算的）
• BUT additive combination of qualitative and
quantitative approaches
（QUAL＋QUAN：足し算的）. ※１＋１＝３
• ※ multiplied ≒ converted （QUAL↔QUAN）
乗算≒データ変換 （質的↔量的）
22
23. (2)Characterizing PAC Analysis
as Explanatory sequential design （2014－2015）
From Creswell and Fetters’ Workshop at MMIRA Conference in Boston College,
2014 to MMIRA in Ritsumeikan U, 2015
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28. (3) Characterizing PAC Analysis
as monostrand or multustrand conversion
design 単線型or複線型変換型混合デザイン
• Seven sequential phases of PAC analysis procedure were
examined whether they have single strand or plural
strands in order to decide whether PAC Analysis is
monostrand conversion quasi-mixed design or multistrand
conversion mixed design. 単線型か複線型か
• A strand 小縄：研究のひとまとまり includes three stages:
1 conceptualization stage, 概念化段階 (=[問題・]目的)
2 experiential stage, データ収集/分析段階（=結果）
3 and inferential stage. 推論段階（=考察[・結論]）
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29. Data conversion データ変換
Data conversion occurs
when collected QUAN data are converted into narratives
or when QUAL data are converted into numbers.
• Quantitizing data: the process of converting QUAL data into
numbers that can be statistically analyzed.
Eg. associated words連想語 →distance matrix距離行列
→dendrogram 樹形図
• Qualitizing data: the process whereby QUAN data are
transformed into narrative data that can be analyzed
qualitatively.
Eg. dendrogram 樹形図→interview 面接→narratives 本人の語り
29
33. ※Text mining as an example of
monostrand conversion design
単線型変換型混合デザインとしてのテキストマイニング
• Quantitizing data: the process of converting
QUAL data（=narrative） into numbers that can
be statistically analyzed (=word count).
• Word frequency analysis単語頻度分析
• Word association analysis係り受け分析
• Word network analysis単語ネットワーク分析
• Positive/ Negative expression analysis 評判分析
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35. Model 1： QUAN to QUAL monostrand
conversion case study method
単線型変換型混合事例研究法
(1) QUAN data collection: 量的データ生成
Phase 1: Word association語連想
Phase 2: Pair words distance rating距離の評定
Phase 3: Cluster analysis (Data 1)クラスター分析による樹形図
(2) Conversion from QUAN to QUAL: 質的データへ変換
Phase 4: Cluster interpretation クラスター解釈
Phase 5: Structural interpretation 全体構造の解釈
（Phase 6: Category table カテゴリー図の生成(Data 2)）
(3) Inference 推論
Phase 7: Discussion/Conclusion考察・結論
35
36. Model 2： QUAN/QUAL multi(bi-)strand
conversion case study method
複線型変換型混合事例研究法
(1) QUAN strand: 量的データ生成
Phase 1: Word association語連想
Phase 2: Pair words distance rating距離の評定
Phase 3: Cluster analysis (Data 1)クラスター分析による樹形図
(2) QUAL strand: 質的データ生成
Phase 4: Cluster interpretation クラスター解釈
Phase 5: Structural interpretation 全体構造の解釈
Phase 6: Category table カテゴリー図の生成(Data 2)
(3) Meta-Inference (Integration) メタ推論
Phase 7: Discussion/Conclusion全体的考察・結論
36
37. Model 3：QUAL/QUAN/QUAL sequential
multi（tri-）strand conversion case study
複々線型変換型混合事例研究法
(1) QUAL strand: 質的データ生成
Phase 1: Word association（Data 1）語連想
(2) QUAN strand: 量的データ生成
Phase 2: Pair words distance rating距離の評定
Phase 3: Cluster analysis (Data 2)クラスター分析による樹形図
(3) QUAL strand: 質的データ生成
Phase 4: Cluster interpretation クラスター解釈
Phase 5: Structural interpretation 全体構造の解釈
Phase 6: Category table カテゴリー図の生成(Data 3)
(4) Meta-Inference (Integration) メタ推論
Phase 7: Discussion/Conclusion全体的考察・結論 37
38. Tentative Conclusion（１）
PAC Analysis can be characterized as either :
• (1) QUAN to QUAL monostrand conversion case study method
単線型変換型混合事例研究法
or
• (2) QUAN/QUAL multi(bi-)strand conversion case study method
複線型変換型混合事例研究法
or
• (3) QUAL/QUAN/QUAL multi（tri-）strand conversion case study
複々線型変換型混合事例研究法
• ※Depending on interpretation of unit of strand
38
39. Tentative Conclusion（2）
PAC Analysis can be characterized as both:
(1) QUAN to QUAL
monostrand conversion
case study method 単線
型変換型混合事例研究
法, if we skip Phase 6
(2) QUAN/QUAL multi(bi-
)strand conversion case
study method 複線型変
換型混合事例研究法 with
Phase 6 (Joint Display)
39
