Maximizing data quality and shortening survey time: Three-form planned missing data survey design

Moore, E. Whitney G.; Lang, Kyle M.; Grandfield, Elizabeth M.

doi:10.1016/j.psychsport.2020.101701

Cited by 14 publications

(15 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a sample survey, data are collected from only a small part of the population unit. The survey was mostly carried out from a representative population sample [15]. The number of students is 143 students.…”

Section: Research Methods 21 Research Designmentioning

confidence: 99%

The use of e-learning in motivating students to excel towards learning outcomes

Lao¹,

Tari²,

Nahas³

et al. 2021

EduLearn

View full text Add to dashboard Cite

Researchers focus on the efforts of teachers to improve learning outcomes. Researchers examined the use of e-learning in motivating student achievement on learning outcomes. The influence of student activity on learning outcomes. Student achievement motivation on learning outcomes. The reason for the low quality of student learning makes the author interested in studying this problem. This paper contributes to using e-learning methods, student activeness, and student achievement motivation and can improve learning outcomes. Researchers find a digital-based learning process, the use of e-learning teaching methods in students' achievement motivation towards learning outcomes. The authors see student learning outcomes after using e-learning. Respondents of the study were 35 students who took Christian religious education subjects. The results of the study revealed that independent use of the material received very high scores. Student activeness is carried out correctly and effectively, the highest perceived to be at a mean value of 4.35. Students who take advantage of e-learning have high learning outcomes. The use of e-learning methods, student activeness, and student achievement motivation is implemented correctly and effectively. It was believed to be able to improve the learning outcomes of Christian Religious Education.

show abstract

Section: Research Methods 21 Research Designmentioning

confidence: 99%

The use of e-learning in motivating students to excel towards learning outcomes

Lao¹,

Tari²,

Nahas³

et al. 2021

EduLearn

View full text Add to dashboard Cite

show abstract

“…The multiform design requires recruiting more participants than a complete data design where all items are administered to all participants. Moore et al (2020) recommended minimum sample size of 300 for the three-form design in cross-sectional studies. The sample size requirement is not surprising.…”

Section: Design Considerationsmentioning

confidence: 99%

“…These variables could include demographic variables, single indicator variables, important covariates, the item(s) that is most representative of key constructs, variables that are potential predictors for unplanned missingness, as well as items known to have unusual distributions (hence missing data on the items will be difficult to handle). However, a recent study argued that a simple assignment strategy that randomly assigns scale items to the X block along with demographics would work well if there are 13 or more items (Lang et al., 2020; Moore, Lang, & Grandfield, 2020). They referred to this approach as a random item assignment (RIA).…”

Section: Item Level Planned Missing Data Designsmentioning

confidence: 99%

See 1 more Smart Citation

Applying planned missingness designs to longitudinal panel studies in developmental science: An overview

Fan

2021

New Directions for Child and Adolescent Development

View full text Add to dashboard Cite

Longitudinal panel studies are widely used in developmental science to address important research questions on human development across the lifespan. These studies, however, are often challenging to implement. They can be costly, time-consuming, and vulnerable to test-retest effects or high attrition over time. Planned missingness designs (PMDs), in which partial data are intentionally collected from all or some of the participants, are viable solutions to these challenges. This article provides an overview of several PMDs with potential utilities in longitudinal studies, including the multi-form designs, multi-method designs, varying lag designs, accelerated longitudinal designs, and efficient designs for analysis of change. For each of the designs, the basic rationale, design considerations, data analysis, advantages, and limitations are discussed. The article is concluded with some general recommendations to developmental researchers and promising directions for future research. K E Y W O R D S accelerated longitudinal designs, efficient designs, longitudinal studies, multi-form designs, planned missingness designs, twomethod designs, varying lag designs Longitudinal panel studies (also termed longitudinal survey studies) are widely used in developmental science to address important research questions on human development across the lifespan. Longitudinal panel studies involve repeatedly collecting measures of target outcomes (e.g., emotional outcomes, gender identity, child abuse, problematic

show abstract

“…Avoiding redundant (highly correlated) predictors in a regression equation and using measures with minimal measurement error (i.e., scales that produce scores considered valid and reliable) are just two of these ways (Lilienfeld & Strother, 2020). Using state of the art techniques to replace missing data to avoid deleting participants is strongly recommended (Little et al, 2014), as well as conducting planned missing data research designs to promote better quality data (Moore et al, 2020). Second, it should be acknowledged that increasing the sample size can make conducting a study more expensive and difficult and can have ethical implications.…”

Section: Limitations Conclusion and Research Implicationsmentioning

confidence: 99%

The N-Pact Factor, Replication, Power, and Quantitative Research in Adapted Physical Activity Quarterly

Martin¹,

Martin²

2021

Kinesiology Review

View full text Add to dashboard Cite

In the current study, a 20-year span of 80 issues of articles (N = 196) in Adapted Physical Activity Quarterly (APAQ) were examined. The authors sought to determine whether quantitative research published in APAQ, based on sample size, was underpowered, leading to the potential for false-positive results and findings that may not be reproducible. The median sample size, also known as the N-Pact Factor (NF), for all quantitative research published in APAQ was coded for correlational-type, quasi-experimental, and experimental research. The overall median sample size over the 20-year period examined was as follows: correlational type, NF = 112; quasi-experimental, NF = 40; and experimental, NF = 48. Four 5-year blocks were also analyzed to show historical trends. As the authors show, these results suggest that much of the quantitative research published in APAQ over the last 20 years was underpowered to detect small to moderate population effect sizes.

show abstract

Maximizing data quality and shortening survey time: Three-form planned missing data survey design

Cited by 14 publications

References 36 publications

The use of e-learning in motivating students to excel towards learning outcomes

The use of e-learning in motivating students to excel towards learning outcomes

Applying planned missingness designs to longitudinal panel studies in developmental science: An overview

The N-Pact Factor, Replication, Power, and Quantitative Research in Adapted Physical Activity Quarterly

Contact Info

Product

Resources

About