The comparative efficacy of imputation methods for missing data in structural equation modeling

Olinsky, Alan; Chen, Shaw; Harlow, Lisa L.

doi:10.1016/s0377-2217(02)00578-7

Cited by 251 publications

(158 citation statements)

References 27 publications

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“…Since the missing data were consistent with the assumption of MAR in this study, statistical analyses were carried out using the FIML, which allows all available information to be used without imputing data (Muthén & Muthén, 1998-2015. Simulation studies show that FIML provides less-biased regression parameter estimates compared to other missing data procedures (Enders, 2001;Olinsky, Chen, & Harlow, 2003). The results of the study will, thus, be reported for the full sample.…”

Section: Aims and Hypothesesmentioning

confidence: 95%

Child-centered versus teacher-directed teaching practices: Associations with the development of academic skills in the first grade at school

Lerkkanen

Kiuru

Pakarinen

et al. 2016

Early Childhood Research Quarterly

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2 Research Highlights How do child-centered versus teacher-directed practices promote academic skills development? Child-centered practices contribute positively to academic skills development at school.  The effect of child-centered practices on academic skills did not depend on the initial skill level  Teacher-directed practices are negatively associated with average and high reading skills. AbstractThis study examined the extent to which child-centered versus teacher-directed teaching practices predicted the development of children's reading and math skills in the first year of elementary school. In addition, we investigated whether associations between teaching practices and children's academic skills development in Grade 1 differed among children who had low, average, or high initial academic skills at the beginning of school. The reading and math skills of 1,132 Finnish children from 93 classrooms were assessed at the beginning and end of Grade 1, and the Early Childhood Classroom Observation Measure (ECCOM) was used to observe teaching practices in 29 classrooms. The results of multilevel modeling showed, first, that better reading skills upon entering school were associated with a higher level of childcentered teaching practices in the classroom. Second, a high level of child-centered teaching practices predicted children's reading and math skills development during the first school year. Third, the results showed that child-centered teaching practices were equally beneficial for the academic skills development of children with varying initial skill levels. However, teacher-directed practices were found to be negatively associated with reading skills development, particularly among children who had average or high initial reading skills at the beginning of school. The results emphasize the importance of childcentered teacher practices in promoting children's academic skills development also after kindergarten in elementary school.Keywords: reading, math, child-centered practices, teacher-directed practices, Grade 1 5 Child-Centered versus Teacher-Directed Teaching Practices:Associations with the Development of Academic Skills in the First Grade at School A considerable body of literature indicates that early childhood education (ECE) classroom practices impact child outcomes (Burchinal et al., 2008;Burchinal, Peisner-Feinberg, Pianta, & Howes, 2002). The majority of this research has been conducted in preschools and kindergartens, but only a few studies have focused on the first school year in depth. For example, a wide range of documentation exists on the positive relationship between child-centered teaching practices and children's social skills and academic pre-skills at the preschool age (Stipek, Feiler, Daniels, & Milburn, 1995). However, children with poor academic skills seem to benefit from teacher-directed practices later on in kindergarten (Huffman & Speer, 2000) and at school age (Kikas, Peets, & Hodges, 2014). The present study examined the extent to which child-centered and teacher-dire...

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Section: Aims and Hypothesesmentioning

confidence: 95%

Child-centered versus teacher-directed teaching practices: Associations with the development of academic skills in the first grade at school

Lerkkanen

Kiuru

Pakarinen

et al. 2016

Early Childhood Research Quarterly

View full text Add to dashboard Cite

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“…Another limitation in this study has been the deletion of incomplete records from the analysis (Little and Rubin 2002). It would be worthwhile to investigate the application of missing data imputation techniques in a subsequent paper (Olinsky et al 2003).…”

Section: Structural Equations Modelling Analysismentioning

confidence: 99%

Vulnerability of a low-income community in South Africa to air pollution: Exploring the use of structural equations modelling to identify appropriate interventions

John

Das

2012

Journal of Integrative Environmental Sciences

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In this study, the relationship between certain household traits and specific environmental health outcome variables was explored in a low-income community from a peri-urban settlement in eMbalenhle, South Africa, with the aim of locating focus areas for targeting appropriate intervention. The susceptibility of this community to environmental pollution-related health outcomes may also be influenced by household-characterizing factors such as nutritional status, hygiene behaviours and other diseases that affect their immune system. Structural equations modelling was used to capture the possible web of relationships between the household traits and a combined respiratory health outcome variable. Specifically, the two traits considered at household level were socioeconomic status and household environment, both of which were latent. Results revealed that primary interventions to improve respiratory health should include converting non-flush toilets to flush toilets, increasing the number of toilets, ensuring regular waste collection, increasing access to medical care and increasing the household income.

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“…While, multiple imputa tion technique is more comprehensive than expectation maximization, it is the most complex of stochastic imputa tion method so far (Schlomer et al 2010). Full Information Maximum Likelihood (FILM), however, represents an al ternative efficient stochastic imputation technique, as it produces unbiased results and estimates accurate standard error and confidence interval by retaining the sample size as well as it produces similar results to each of EM and MI (Enders, Bandalos 2001;Olinsky et al 2003). From another standpoint, while scholars consider that FIML is an effici ent technique and one of the preferred methods for handle missing data (Enders, Bandalos 2001;Schlomer et al 2010), others believe that MI is probably most promising, because of its theoretical and distributional underpinnings, while FIML is a direct model based method for estimating para meters in the presence of missing data and does not actually impute the missing data (Olinsky et al 2003).…”

Section: Missing Data: Better To Manage Not To Damagementioning

confidence: 99%

“…Full Information Maximum Likelihood (FILM), however, represents an al ternative efficient stochastic imputation technique, as it produces unbiased results and estimates accurate standard error and confidence interval by retaining the sample size as well as it produces similar results to each of EM and MI (Enders, Bandalos 2001;Olinsky et al 2003). From another standpoint, while scholars consider that FIML is an effici ent technique and one of the preferred methods for handle missing data (Enders, Bandalos 2001;Schlomer et al 2010), others believe that MI is probably most promising, because of its theoretical and distributional underpinnings, while FIML is a direct model based method for estimating para meters in the presence of missing data and does not actually impute the missing data (Olinsky et al 2003). However, full information maximum likelihood (FIML) is a superior met hod comparing to multiple imputation (MI), as its ability to manage missing data and conduct analyses in one step, as well as it is a superior method comparing to expecta tion maximization (EM), as its ability to estimate accurate standard errors and confidence intervals by retaining the sample size.…”

Section: Missing Data: Better To Manage Not To Damagementioning

confidence: 99%

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A Pilot Study: Vital Methodological Issues

Hazzi

Maldaon

2015

Business: Theory and Practice

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Abstract.A pilot study represents a vital step for conducting a full fledged study soundly. In fact, a well conducted pilot study can help the researchers to design a clear road map they can follow. Conducting a pilot study professionally, however, involves vital quantitative methodological issues (i.e., Back Translation, Missing Data, Normality, and Reliability) the researchers had better take into account when conducting the pilot study and before embarking the main one. Unfortunately, such issues are neglected in many researches as well as barely addressed together in a one work in research papers. From the literature and the experience, the present work aims to address the most recommended practices of such methodological issues providing at the same time the best practices for new researchers and scholars alike, with a view to reduce the loss of suffered by research com munity when such issues and practices remain unpublished together. Suggestions and thoughts were also demonstrated in this work for further researches. Finally, the importance of such research for business sector was also demonstrated in this work.

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The comparative efficacy of imputation methods for missing data in structural equation modeling

Cited by 251 publications

References 27 publications

Child-centered versus teacher-directed teaching practices: Associations with the development of academic skills in the first grade at school

Child-centered versus teacher-directed teaching practices: Associations with the development of academic skills in the first grade at school

Vulnerability of a low-income community in South Africa to air pollution: Exploring the use of structural equations modelling to identify appropriate interventions

A Pilot Study: Vital Methodological Issues

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