Modern Alternatives for Dealing with Missing Data in Special Education Research

Enders, Craig K.; Dietz, Samantha; Montague, Marjorie; Dixon, J. Faye

doi:10.1016/s0735-004x(06)19005-9

Cited by 24 publications

(24 citation statements)

References 15 publications

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“…A preliminary investigation of the data revealed that 20 percent of the possible responses on predictor variables were missing at random (Enders et al. ; Little and Rubin ). I used multiple imputation by chained equation (MICE) to handle this missing data (Little and Rubin 1989–90; Rubin ).…”

mentioning

confidence: 99%

A Field Study of the Presumptively Biased: Is There Empirical Support for Excluding Convicted Felons from Jury Service?

Binnall¹

2013

Law & Policy

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confidence: 99%

A Field Study of the Presumptively Biased: Is There Empirical Support for Excluding Convicted Felons from Jury Service?

Binnall¹

2013

Law & Policy

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“…Consequently, the ulterior analysis is directly designed based on the raw data [15]. It is poor when the percentage of missing values per attribute varies considerably.…”

Section: Related Workmentioning

confidence: 99%

“…It consists of replacing the unknown value for a given attribute by the mean (quantitative attribute) or mode (qualitative attribute) of all known values of that attribute. Replacing all missing records with a single value distorts the input data distribution [15]. …”

Section: Related Workmentioning

confidence: 99%

Clustering‐Based Multiple Imputation via Gray Relational Analysis for Missing Data and Its Application to Aerospace Field

Tian

et al. 2013

The Scientific World Journal

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A large number of scientific researches and industrial applications commonly suffer from missing data. Some inappropriate techniques of missing value treatment compromise data quality, which detrimentally influences the knowledge discovery. In this paper, we propose a missing data completion method named CBGMI. Firstly, it separates the nonmissing data instances into several clusters by excluding the missing-valued entries. Then, it utilizes the entropy of the proximal category for each incomplete instance in terms of the similarity metric based on gray relational analysis. Experiments on UCI datasets and aerospace datasets demonstrate that the superiority of our algorithm to other approaches on validity.

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“…Excluding case data reduces the size of the sample and the degrees of freedom, loses statistical power, and omits valuable data particularly in small population surveys (Dodeen, 2003;Enders, et al, 2006;Hair, et al, 2006;Molenberghs, 2007;Raaijmakers, 1999 approximately the same weighting (not increasing in complexity) (Dodeen, 2003).…”

Section: Resolving Continuity Issues and Maintaining Data Integritymentioning

confidence: 99%

Timely Intervention – Before It’s Too Hard

Clarke¹

2012

Reflections on Learning, Life and Work

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Students who have difficulty conforming to school rules and expected school behavioural norms are at risk of being excluded from their own schools, and possibly from further education. Failure to complete twelve years of schooling places the students at a social and economic disadvantage for the rest of their lives.Intervention programs attempt to address students' behavioural and social issues and assist them to maintain their connection with education. This thesis examines an intervention program in Melbourne, Australia which is staffed by special education teachers and located away from the home schools of the students.Inappropriate student behaviours were identified from a review of the intervention unit's historical records. These behaviours were then compared and aligned with earlier analyses of difficult behaviours, in particular the categories from the Achenbach Child Behaviour Check List.Quantitative analysis methods were used to validate the Behaviour Rating Scale that was developed to measure pre and post intervention behaviour. The Behaviour Rating Scale outcomes were used in conjunction with a Sessional Evaluation Measure (SEM) to assess the effectiveness of the off-site intervention program.The thesis concludes with a model identifying key elements of effective intervention programs based on both investigations undertaken and the literature reviewed.iv

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Modern Alternatives for Dealing with Missing Data in Special Education Research

Cited by 24 publications

References 15 publications

A Field Study of the Presumptively Biased: Is There Empirical Support for Excluding Convicted Felons from Jury Service?

A Field Study of the Presumptively Biased: Is There Empirical Support for Excluding Convicted Felons from Jury Service?

Clustering‐Based Multiple Imputation via Gray Relational Analysis for Missing Data and Its Application to Aerospace Field

Timely Intervention – Before It’s Too Hard

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