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Huisman, Mark; Krol, Bianca; Sonderen, van Eric

doi:10.1023/a:1004338522505

Cited by 16 publications

(1 citation statement)

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“…It follows, therefore, that an issue prevalent in this study is that the considered training-retention data set is sparse, because each response from an SME owner/manager could be one of two forms of responses, either that they used the TA and gave a Likert-scale-based score on the level of satisfaction towards it or the SME did not use that TA so no score given. As such, the data are understandably sparse, an issue that can cause problems for the ability to pertinently analyse them using traditional analysis techniques (Huisman et al, 1998;Schafer and Graham, 2002;Olinsky et al, 2003;Di Nuovo, 2011).…”

Section: Introductionmentioning

confidence: 99%

Investigating the impact of training influence on employee retention in small and medium enterprises: a regression‐type classification and ranking believe simplex analysis on sparse data

et al. 2014

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This study investigates the impact of available training alternatives (TAs) on employee retention in small and medium enterprises (SMEs). A noticeable problem with this research issue is that individual SMEs may utilize different combination of TAs. The considered survey questionnaire allowed respondent SME owners/managers the option to gauge the level of satisfaction of a TA or to indicate that they did not use it. It follows, therefore, that the survey‐based data set is sparse, in the sense that the ‘did not use’ option infers that a form of missing value is present (Likert‐scale‐based satisfaction value present if a TA was used). To facilitate an effective analysis of the considered sparse data set, because the missing values have meaning, the nascent regression‐type classification and ranking believe simplex (RCaRBS) technique is employed. As a development of the CaRBS technique, this technique is able to undertake multivariate regression‐type analysis on sparse data, without the need to manage the missing values in any way. Results are presented from the RCaRBS analyses relating to SME owner/managers' satisfactions with TAs and their impact on two employee retention facets, namely greater employee loyalty and, conversely, losing an employee to a competitor. Emphasis here is on the graphical elucidation of findings in regard to model fit and TA contribution. The pertinence of the study is the inclusiveness of the data considered (a novel approach to analysing sparse data), and the comparisons between these associated issues of TA satisfaction and employee retention.

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Section: Introductionmentioning

confidence: 99%

Investigating the impact of training influence on employee retention in small and medium enterprises: a regression‐type classification and ranking believe simplex analysis on sparse data

et al. 2014

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Intention‐to‐treat in randomized controlled trials: Recommendations for a total trial strategy

Polit

Gillespie

2010

Research in Nursing & Health

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Intention-to-treat (ITT) in randomized controlled trials involves keeping participants in the treatment groups to which they were randomized regardless of whether they withdraw following randomization. Intention-to-treat is a strategy for maintaining the integrity of randomization and strengthening the trial's internal validity. Although ITT is advocated by the Consolidated Standards of Reporting Trials (CONSORT) guidelines, there is confusion about what ITT means and little specific advice on how to achieve it. The purpose of this article is to present definitions of ITT and to suggest strategies for implementing ITT as a total design strategy in nursing clinical trials. Recommendations are offered regarding study planning, study design, subject retention, sampling, data collection, data analysis, and reporting within the context of ITT.

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Systematic Measurement Error

Mellenbergh

2019

Counteracting Methodological Errors in Behavioral Research

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Cited by 16 publications

References 3 publications

Investigating the impact of training influence on employee retention in small and medium enterprises: a regression‐type classification and ranking believe simplex analysis on sparse data

Investigating the impact of training influence on employee retention in small and medium enterprises: a regression‐type classification and ranking believe simplex analysis on sparse data

Intention‐to‐treat in randomized controlled trials: Recommendations for a total trial strategy

Systematic Measurement Error

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