-
1
-
-
0004093524
-
-
Thousand Oaks, CA: Sage
-
Allison, P.D. (2001). Missing data. Thousand Oaks, CA: Sage.
-
(2001)
Missing Data
-
-
Allison, P.D.1
-
2
-
-
0345475379
-
Missing data techniques for structural equation modeling
-
Allison, P.D. (2003). Missing data techniques for structural equation modeling. Journal of Abnormal Psychology, 112, 545-557.
-
(2003)
Journal of Abnormal Psychology
, vol.112
, pp. 545-557
-
-
Allison, P.D.1
-
3
-
-
0002914202
-
Full information estimation in the presence of incomplete data
-
In G. A. Marcoulides & R. E. Schumacker (Eds.), Mahwah, NJ: Lawrence Erlbaum
-
Arbuckle, J.L. (1996). Full information estimation in the presence of incomplete data. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling (pp. 243-277). Mahwah, NJ: Lawrence Erlbaum.
-
(1996)
Advanced Structural Equation Modeling
, pp. 243-277
-
-
Arbuckle, J.L.1
-
4
-
-
0032954507
-
Applications of multiple imputation in medical studies: From AIDS to NHANES
-
Barnard, J., & Meng, X. (1999). Applications of multiple imputation in medical studies: From AIDS to NHANES. Statistical Methods in Medical Research, 8, 17-36.
-
(1999)
Statistical Methods in Medical Research
, vol.8
, pp. 17-36
-
-
Barnard, J.1
Meng, X.2
-
5
-
-
0000783293
-
Efficacy of the indirect approach for estimating structural equation models with missing data: A comparison of five methods
-
Brown, R.L. (1994). Efficacy of the indirect approach for estimating structural equation models with missing data: A comparison of five methods. Structural Equation Modeling, 1, 287-316.
-
(1994)
Structural Equation Modeling
, vol.1
, pp. 287-316
-
-
Brown, R.L.1
-
6
-
-
0035755636
-
A comparison of inclusive and restrictive strategies in modern missing data procedures
-
Collins, L.M., Schafer, J.L., & Kam, C. (2001). A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychological Methods, 6, 330-351.
-
(2001)
Psychological Methods
, vol.6
, pp. 330-351
-
-
Collins, L.M.1
Schafer, J.L.2
Kam, C.3
-
7
-
-
0035756118
-
The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data
-
Enders, C.K. (2001). The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data. Psychological Methods, 6, 352-370.
-
(2001)
Psychological Methods
, vol.6
, pp. 352-370
-
-
Enders, C.K.1
-
8
-
-
33645894571
-
Analyzing structural equation models with missing data
-
In G. Hancock & R. Mueller (Eds.), Greenwich, CT: Information Age
-
Enders, C.K. (2006). Analyzing structural equation models with missing data. In G. Hancock & R. Mueller (Eds.), Structural equation modeling: A second course (pp. 313-342). Greenwich, CT: Information Age.
-
(2006)
Structural Equation Modeling: A Second Course
, pp. 313-342
-
-
Enders, C.K.1
-
9
-
-
0000885702
-
The relative performance of full information maximum likelihood estimation for missing data in structural equation models
-
Enders, C.K., & Bandalos, D.L. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Structural Equation Modeling, 8, 430-457.
-
(2001)
Structural Equation Modeling
, vol.8
, pp. 430-457
-
-
Enders, C.K.1
Bandalos, D.L.2
-
10
-
-
2642541763
-
Using an EM covariance matrix to estimate structural equation models with missing data: Choosing an adjusted sample size to improve the accuracy of inferences
-
Enders, C.K., & Peugh, J.L. (2004). Using an EM covariance matrix to estimate structural equation models with missing data: Choosing an adjusted sample size to improve the accuracy of inferences. Structural Equation Modeling, 11, 1-19.
-
(2004)
Structural Equation Modeling
, vol.11
, pp. 1-19
-
-
Enders, C.K.1
Peugh, J.L.2
-
11
-
-
0004012196
-
-
London: Chapman & Hall
-
Gelman, A., Carlin, J.B., Stern, H.S., & Rubin, D.B. (1995). Bayesian data analysis. London: Chapman & Hall.
-
(1995)
Bayesian Data Analysis
-
-
Gelman, A.1
Carlin, J.B.2
Stern, H.S.3
Rubin, D.B.4
-
12
-
-
0000497010
-
Treatments of missing data: A Monte Carlo comparison of RBHDI, iterative stochastic regression imputation, and expectation-maximization
-
Gold, M.S., & Bentler, P.M. (2000). Treatments of missing data: A Monte Carlo comparison of RBHDI, iterative stochastic regression imputation, and expectation-maximization. Structural Equation Modeling, 7, 319-355.
-
(2000)
Structural Equation Modeling
, vol.7
, pp. 319-355
-
-
Gold, M.S.1
Bentler, P.M.2
-
13
-
-
3042829565
-
A comparison of maximum-likelihood and asymptotically distribution-free methods of treating incomplete nonnormal data
-
Gold, M.S., Bentler, P.M., & Kim, K.H. (2003). A comparison of maximum-likelihood and asymptotically distribution-free methods of treating incomplete nonnormal data. Structural Equation Modeling, 10, 47-79.
-
(2003)
Structural Equation Modeling
, vol.10
, pp. 47-79
-
-
Gold, M.S.1
Bentler, P.M.2
Kim, K.H.3
-
14
-
-
0347249765
-
Adding missing-data-relevant variables to FIML-based structural equation models
-
Grahan, J.W. (2003). Adding missing-data-relevant variables to FIML-based structural equation models. Structural Equation Modeling, 10, 80-100.
-
(2003)
Structural Equation Modeling
, vol.10
, pp. 80-100
-
-
Grahan, J.W.1
-
15
-
-
33846873244
-
Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models
-
Horton, N.J., & Kleinman, K.P. (2007). Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models. The American Statistician, 61, 79-90.
-
(2007)
The American Statistician
, vol.61
, pp. 79-90
-
-
Horton, N.J.1
Kleinman, K.P.2
-
18
-
-
0040731105
-
Pairwise deletion for missing data in structural equation models: Nonpositive definite matrices, parameter estimates, goodness of fit, and adjusted sample sizes
-
Marsh, H.W. (1998). Pairwise deletion for missing data in structural equation models: Nonpositive definite matrices, parameter estimates, goodness of fit, and adjusted sample sizes. Structural Equation Modeling, 5, 22-36.
-
(1998)
Structural Equation Modeling
, vol.5
, pp. 22-36
-
-
Marsh, H.W.1
-
19
-
-
15244345570
-
A short version of the Self Description Questionnaire II: Operationalizing criteria for short-form evaluation with new applications of confirmatory factor analyses
-
Marsh, H.W., Ellis, L., Parada, L., Richards, G., & Heubeck, B.G. (2005). A short version of the Self Description Questionnaire II: Operationalizing criteria for short-form evaluation with new applications of confirmatory factor analyses. Psychological Assessment, 17, 81-102.
-
(2005)
Psychological Assessment
, vol.17
, pp. 81-102
-
-
Marsh, H.W.1
Ellis, L.2
Parada, L.3
Richards, G.4
Heubeck, B.G.5
-
20
-
-
0001010853
-
On structural equation modeling with data that are not missing completely at random
-
Muthen, B., Kaplan, D., & Hollis, M. (1987). On structural equation modeling with data that are not missing completely at random. Psychometrika, 52, 431-462.
-
(1987)
Psychometrika
, vol.52
, pp. 431-462
-
-
Muthen, B.1
Kaplan, D.2
Hollis, M.3
-
21
-
-
0038009574
-
Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques
-
Newman, D.A. (2003). Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques. Organizational Research Methods, 6, 328-362.
-
(2003)
Organizational Research Methods
, vol.6
, pp. 328-362
-
-
Newman, D.A.1
-
22
-
-
0041589601
-
The comparative efficacy of imputation methods for missing data in structural equation modeling
-
Olinsky, A., Chen, S., & Harlow, L. (2003). The comparative efficacy of imputation methods for missing data in structural equation modeling. European Journal of Operational Research, 15, 53-79.
-
(2003)
European Journal of Operational Research
, vol.15
, pp. 53-79
-
-
Olinsky, A.1
Chen, S.2
Harlow, L.3
-
24
-
-
0003526297
-
-
SAS Institute., Cary, NC: SAS Institute
-
SAS Institute. (2001). The SAS system for windows. Cary, NC: SAS Institute.
-
(2001)
The SAS System for Windows
-
-
-
25
-
-
18444385925
-
A statistically justified pairwise ML method for incomplete nonnormal data: A comparison with direct ML and pairwise ADF
-
Savalei, V., & Bentler, P.M. (2005). A statistically justified pairwise ML method for incomplete nonnormal data: A comparison with direct ML and pairwise ADF. Structural Equation Modeling, 12, 183-214.
-
(2005)
Structural Equation Modeling
, vol.12
, pp. 183-214
-
-
Savalei, V.1
Bentler, P.M.2
-
28
-
-
85047673373
-
Missing data: Our view of the state of the art
-
Schafer, J.L., & Graham, J.W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147-177.
-
(2002)
Psychological Methods
, vol.7
, pp. 147-177
-
-
Schafer, J.L.1
Graham, J.W.2
-
29
-
-
0032219074
-
Multiple imputation for multivariate missing data problems: A data analyst's perspective
-
Schafer, J.L., & Olsen, M.K. (1998). Multiple imputation for multivariate missing data problems: A data analyst's perspective. Multivariate Behavioral Research, 33, 545-571.
-
(1998)
Multivariate Behavioral Research
, vol.33
, pp. 545-571
-
-
Schafer, J.L.1
Olsen, M.K.2
-
30
-
-
0033616909
-
Multiple imputation of missing blood pressure covariates in survival analysis
-
Van Buuren, S., Boshuizen, H.C., & Knook, D.L. (1999). Multiple imputation of missing blood pressure covariates in survival analysis. Statistics in Medicine, 18, 681-694.
-
(1999)
Statistics in Medicine
, vol.18
, pp. 681-694
-
-
van Buuren, S.1
Boshuizen, H.C.2
Knook, D.L.3
-
31
-
-
0002298117
-
Longitudinal and multi-group modeling with missing data
-
In T. D. Little, K. U. & J. Baumer (Eds.), Mahwah, NJ: Lawrence Erlbaum
-
Wothke, W. (2000). Longitudinal and multi-group modeling with missing data. In T. D. Little, K. U. Schnabel, & J. Baumer (Eds.), Modeling longitudinal and multiple group data: Practical issues, applied approaches, and specific examples (pp. 219-240). Mahwah, NJ: Lawrence Erlbaum.
-
(2000)
Modeling Longitudinal and Multiple Group Data: Practical Issues, Applied Approaches, and Specific Examples
, pp. 219-240
-
-
Wothke, W.1
Schnabel2
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