8. 事例 慢性閉塞性肺疾患(COPD)者のQOL尺度
Scale content was generated from qualitative, unstructured interviews
conducted with patients with COPD in the UK and focus groups with patients
in the USA. The interviewees and focus group participants were encouraged
to talk at length about their experience of COPD and the impact of the
disease on all areas of their life.
Audio recordings were made of the interviews and focus group discussions.
These were transcribed, and each interview was subjected to content analysis
by at least two experienced qualitative researchers to identify statements
expressing the impact of LCOPD on patient’s lives.
The needs-based model of QoL were employed for the LCOPD [13]. This model
asserts that QoL is dependent on an individual’s ability to fulfil his or her
fundamental needs and that QoL is good when most needs are met and poor
when they are not.
モデルの選択⇒QOLの欲求ベースモデルを採用
患者への面接による項目収集
専門家の判断による項目の吟味
McKenna SP et al: Qual Life Res (2011) 20:1043–1052
内容的妥当性 構造的妥当性 仮説検証
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9. 事例 慢性閉塞性肺疾患(COPD)者のQOL尺度
It was clear from the interviews that COPD has a considerable adverse impact on
many aspects of the lives of affected individuals. Figure 1 shows the conceptual
framework for the LCOPD, illustrating how the issues raised during the
interviews relate to needs and quality of life impact.
患者へのインタビューから,COPD患者のQOLモデルを構築
Cognitive debriefing interviews
were conducted with 19 patients
in the UK and 16 in the USA.
Demographic details of the
sample are shown in Table 1. The
questionnaires were well
received by participants who
found them relevant,
comprehensible, easy and quick
to complete.
項目の関連性・包括性を患者が確認
McKenna SP et al: Qual Life Res (2011) 20:1043–1052
内容的妥当性 構造的妥当性 仮説検証
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10. 事例 患者の報告が包括性に重要
Jonesa, P et al: Primary Care Respiratory Journal (2009); 18(3): 208-215
文献レビューによる概念の定義
専門家への電話面接によって患者
の健康の指標となる項目を聴取
患者のインタビューに基づく項目と
専門家による項目の確認
項目の作成手順
内容的妥当性 構造的妥当性 仮説検証
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19. ・事例
Explanatory factor analysis (EFA)
was used to examine the
dimensionality of the item set
measuring the underlying construct,
because the results suggested
insufficient model fit [27, 28].
S. A. M. Stevelink et al: Qual Life Res (2013) 22:137–144
(EFAとCFAの使い分け)
CFAで理論に基づき因子構造を検討
CFAの結果が不良
EFAで探索的に検討
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22. 共分散構造分析
適合度指標
絶対的指標: データとモデルの共分散行列の類似度
(absolute indices)
増分的指標: 独立モデルと比較して,分析モデルによって
(incremental indices) データの適合が改善した度合い
倹約的指標: モデルの複雑さを考慮した,モデルのデータ
(parsimonious indices) に対する近似度
指標 内容 基準
SRMR モデルで説明できなかった分散の大きさ .08以下
CFI 自由度を考慮した乖離度の改善の大きさ .95以上
RMSEA 1自由度あたりの乖離度の大きさ .05以下
Ralph, O et al (2008): The Reviewer‘s Guide to Quantitative Methods in the Social Sciences
内容的妥当性 構造的妥当性 仮説検証
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23. 事例 (適合度指標)
Four practical fit indices were used to evaluate model fit: the
Tucker-Lewis index (TLI), the comparative fit index (CFI), the root
mean square error of approximation (RMSEA), and the standardized
root-mean-square residual (SRMR). Guidelines proposed by Hu
and Bentler (13) suggest that models with TLI and CFI close to
0.95 or higher, RMSEA close to 0.06 or lower, and SRMR close
to 0.08 or lower are representative of good-fitting models.
方法の節 (指標の適合基準の参照元を明示する)
結果の節(他のモデルと比較して仮説モデルが妥当か評価)
Thombs et al: Arthritis & Rheumatism Vol. 59, No. 3, March 15, 2008, pp 438–443
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24. 事例 (高次(2次)因子モデルの適用)
Thombs et al: Arthritis & Rheumatism Vol. 59, No. 3, March 15, 2008, pp 438–443
hopeful
good
unfriendly
disliked
enjoy
happy
IP PA S/V DA
sleep
effort
Getgoing
Talkedless
appetite
botjered
mind
lonely
fearful
sad
cry
depressed
Blues
failure
Depressive
symptom
1次因子間の相関を少数の2次因子で説明
適用ケース
>上位概念が想定される場合
>因子間相関が高い場合
Second-order factors are global
factors composed of all of the first-
order factors (e.g., depressed affect,
somatic/vegetative, (lack of) positive
affect, and interpersonal) that
provide a mechanism to test the
plausibility that a single overarching
construct is being measured.
方法の節 (高次因子分析)
内容的妥当性 構造的妥当性 仮説検証
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28. 探索的因子分析
・事例 方法の節
To minimize potential for over- or under-identification of factors,
parallel analysis (e.g., Brown, 2006) and Velicer‘s MAP (Velicer,
1976) were computed. Parallel analysis computes randomly
generated data sets to specifications and compares the obtained
eigenvalues in the raw data to those obtained by chance (see
O’Connor, 2000; Brown, 2006). Velicer‘s MAP is a step-wise
process whereby components are partialed out of the correlation
matrix sequentially. The step corresponding to the lowest partial
squared correlation indicates the number of components (see
Velicer, 1976; O’Connor, 2000). Parallel analysis using normally
distributed random data generated 1000 datasets limited to the
95th percentile with principal components analysis (O‘Connor,
2000).
N.T. Van Dam, M. Earleywine: Psychiatry Research 186 (2011) 128–132
内容的妥当性 構造的妥当性 仮説検証
28
29. 探索的因子分析
・事例 結果の節
N.T. Van Dam, M. Earleywine: Psychiatry Research 186 (2011) 128–132
Parallel analysis suggested four roots with eigenvalues larger than what would
be obtained by chance. Velicer's MAP revealed a smallest average squared partial
correlation of 0.020 on step two suggesting two underlying components.
Maximum Likelihood estimation using promax rotation limited to two-, three-,
and four-factor solutions was used to explore factor loadings. Examination of
the three- and four factor solutions revealed inconsistencies with theoretical
considerations and optimal psychometric properties (see Brown, 2006). Both
solutions suggested a factor containing only three items (1, 5, 19) related to appetite
and sleep. This factor excluded another item related to sleep (11) and one related
to weight changes (18), suggesting substantive inconsistencies.
The two-factor solution was both theoretically and psychometrically consistent,
suggesting one factor related to negative mood and another factor related to
functional impairment.
平行分析で4因子・MAPで2因子
3・4因子は理論的と不一致
2因子解が理論・統計的な一貫性が良い
内容的妥当性 構造的妥当性 仮説検証
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32. 質的変数の相関イメージ(テトラコリック相関)
a b
c
d
t1
t2
y1
y2
評定者2
うつ病無 うつ病あり
評定者1
うつ病無 a b a+b
うつ病あり c d c+d
a+c b+d 1
③クロス集計表の実測値と近似する
楕円の範囲を推定 (2段階最尤推定法)
②2者の評定によるクロス集計表①名義(2値)尺度の背後に連続量を仮定
In contrast to a classical CFA which uses the
covariance matrix, CFA uses the polychoric
correlations. We used the weighted least squares
(WLS) method of estimation.
論文での記載事例(質的因子分析)
Mokkink et al (2011): Multiple Sclerosis Journal 17(12) 1498–1503
内容的妥当性 構造的妥当性 仮説検証
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42. ① 概念の記述
② 仮説の定式化
③ 比較尺度 or 対象群を記述
④ データ収集
⑤ 結果と仮説の整合性を評価
⑥ 結果の説明
検討手続き
内容的妥当性 構造的妥当性 仮説検証
42
43. ② 仮説の定式化: 事例
The hypotheses were based on the literature and theoretical
considerations and were agreed on by all authors before
they were tested. As in previous observations, we did not
expect to find correlation coefficients of more than 0.50. If a
relationship was anticipated, we expected to find correlation
coefficients between 0.21 and 0.50. These cutoff values were
arbitrarily chosen, but are in line with general recommendations
for weak associations. 53,54
仮説 (方向性・程度を含む)仮説 (方向性・程度を含む)
Apeldoorn et al: Clin J Pain Volume 28, Number 4, May 2012
程度の基準を明記
内容的妥当性 構造的妥当性 仮説検証
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44. 事例:仮説設定
Several studies have concluded that there is a link between high
Waddell scores and depression,15,17,31,37,50 but 1 other study found no
association.33 In this study, depression was measured with the Dutch
translation of the Beck Depression Inventory (BDI).67,68 The BDI
consists of 21 graded items, ranging in severity from 0 to 3. It has
good psychometric properties for the measurement of depression,
but in patients with CLBP a confounding effect has been found for 3
items measuring somatic symptoms.69 In this study, we expected to
find a positive association between high Waddell scores and
elevated BDI scores.
比較尺度の特性および仮説
Apeldoorn et al: Clin J Pain Volume 28, Number 4, May 2012
内容的妥当性 構造的妥当性 仮説検証
44
48. SEMによるMTMM
B1A1 C1
trait A
B2A2 C2
trait B
B3A3 C3
trait C
method
1
method
2
method
3
model 1: 多特性・多方法モデル (加法モデル)
freely correlated trait and method
内容的妥当性 構造的妥当性 仮説検証
Byrne, B. M. (2011). Structural Equation Modeling with Mplus: Basic Concepts, Applications,
and Programming (Multivariate Applications Series). Routledge Academic 48
49. SEMによるMTMM (比較モデル)
model 2: 特性を想定しないモデル
no trait – freely correlated method
B1A1 C1 B2A2 C2 B3A3 C3
method
1
method
2
method
3
内容的妥当性 構造的妥当性 仮説検証
Byrne, B. M. (2011). Structural Equation Modeling with Mplus: Basic Concepts, Applications,
and Programming (Multivariate Applications Series). Routledge Academic 49
50. SEMによるMTMM(比較モデル)
model 3: 概念の弁別性を想定しないモデル
perfectly correlated traits – freely correlated methods
B1A1 C1
trait
B2A2 C2 B3A3 C3
method
1
method
2
method
3
内容的妥当性 構造的妥当性 仮説検証
Byrne, B. M. (2011). Structural Equation Modeling with Mplus: Basic Concepts, Applications,
and Programming (Multivariate Applications Series). Routledge Academic 50
51. SEMによるMTMM (比較モデル)
model 4: 測定方法の違いを想定しないモデル
freely correlated traits – perfectly correlated methods
B1A1 C1
trait A
B2A2 C2
trait B
B3A3 C3
trait C
method
内容的妥当性 構造的妥当性 仮説検証
Byrne, B. M. (2011). Structural Equation Modeling with Mplus: Basic Concepts, Applications,
and Programming (Multivariate Applications Series). Routledge Academic 51
52. SEMによるMTMM
>
model 1 model 2
収束的妥当性がある場合
B1A1 C1
trait A
B2A2 C2
trait B
B3A3 C3
trait C
method
1
method
2
method
3
B1A1 C1 B2A2 C2 B3A3 C3
method
1
method
2
method
3
内容的妥当性 構造的妥当性 仮説検証
52
Langer et al. (2010). Child Psychiatry and Human
Development, 41, 549–561.
53. SEMによるMTMM
>
弁別的妥当性がある場合
model 1
model 2
model 3
B1A1 C1
trait
B2A2 C2 B3A3 C3
method
1
method
2
method
3
B1A1 C1
trait A
B2A2 C2
trait B
B3A3 C3
trait C
method
B1A1 C1
trait A
B2A2 C2
trait B
B3A3 C3
trait C
method
1
method
2
method
3
内容的妥当性 構造的妥当性 仮説検証
53
54. B1A1 C1
trait A
B2A2 C2
trait B
B3A3 C3
trait C
e
1
e
2
e
3
e
4
e
5
e
6
e
7
e
8
e
9
MTMM modelは”解が収束しない/不適解”がよく生じる
代替法 ⇒ correlated uniqueness model(CUM)
SEMによるMTMM
内容的妥当性 構造的妥当性 仮説検証
Kenny, D. A. & Kashy, D. A. Psychological Bulletin, Vol 112(1), Jul 1992, 165-172.54
58. Apeldoorn, A. T., Ostelo, R. W., Fritz, J. M., van der Ploeg, T., van Tulder, M. W., & de Vet, H. C. (2012). The cross-
sectional construct validity of the Waddell score. Clinical Journal of Pain, 28, 309-17.
Byrne, B. M. (2011). Structural Equation Modeling with Mplus: Basic Concepts, Applications,
and Programming (Multivariate Applications Series). Routledge Academic
Campbell, D. T. & Fiske, D.W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix.
Psychological Bulletin, 56, 81-105.
Henson, R. K. & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: common errors and
some comment on improved practice. Educational and Psychological Measurement, 66, 393-416.
Jones, P., Harding, G., Wiklund, I., Berry, P., & Leidy, N. (2009). Improving the process and outcome of care in
COPD: development of a standardized assessment tool. Primary Care Respiratory Journal, 18, 208-215.
Kenny, D. A. & Kashy, D. A. (1992). Analysis of the multitrait-multimethod matrix by confirmatory factor analysis.
Psychological Bulletin, 112, 165-172.
Langer, D. A., Wood, J. J., Bergman, R. L., & Piacentini, J. C. (2010). A Multitrait–Multimethod Analysis of the
Construct Validity of Child Anxiety Disorders in a Clinical Sample. Child Psychiatry and Human Development,
41, 549–561.
McKenna, S. P., Meads, D. M., Doward, L. C., Twiss, J., Pokrzywinski, R., Revicki, D., Hunter, C. J., &
Glendenning, G. A. (2011) Development and validation of the living with chronic obstructive pulmonary disease
questionnaire. Qualty of Life Research, 20, 1043–1052
Mokkink, L. B., Knol, D. L., & Uitdehaag, B. M. J. (2011). Factor structure of Guy's Neurological Disability Scale in
a sample of Dutch patients with multiple sclerosis. Multiple Sclerosis Journal, 17, 1498–1503.
Meuller R. O. & Hancock, G. R. (2010). Structural equation modeling. G. R. Hancock & R. O. Mueller (Eds.), The
reviewer's guide to quantitative methods in the social sciences. New York: Routledge, Pp. 371-383.
Stevelink, S. A. M., Terwee, C. B., Banstola, N., & van Brakel, W. H. (2013). Testing the psychometric properties of
the Participation Scale in Eastern Nepal. Quality of Life Research, 22, 137–144.
Thombs, T. B., Hudson, M., Schieir, O., Taillefer, S. S., & Baron, M. (2011). Reliability and validity of the center for
epidemiologic studies depression scale in patients with systemic sclerosis. Arthritis Care & Research, 59, 438–443.
Van Dam, N. T. & Earleywine, M. (2011). Validation of the Center for Epidemiologic Studies Depression Scale-
Revised (CESD-R): pragmatic depression assessment in the general population. Psychiatry Research, 30, 128-132.
Vet, H. C. W., Terwee, C. B., Mokkink, L. B., & Knol, D. J. (2011) Measurement in medicine. A practical guide.
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