Blar i BI Open på forfatter "Foldnes, Njål"
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A PROBLEM WITH DISCRETIZING VALE–MAURELLI IN SIMULATION STUDIES
Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2019)Previous influential simulation studies investigate the effect of underlying non-normality in ordinal data using the Vale–Maurelli (VM) simulation method. We show that discretized data stemming from the VM method with a ... -
A qualitative investigation of student engagement in a flipped classroom
Steen-Utheim, Anna Therese; Foldnes, Njål (Journal article; Peer reviewed, 2018)The flipped classroom is gaining acceptance in higher education as an alternative to more traditional methods of teaching. In the current study, twelve students in a Norwegian higher education institution were in-depth ... -
A simple simulation technique for nonnormal data with prespecified skewness, kurtosis, and covariance matrix
Foldnes, Njål; Olsson, Ulf Henning (Journal article; Peer reviewed, 2016)We present and investigate a simple way to generate non-normal data using linear combinations of independent generator (IG) variables. The simulated data have prespecified univariate skewness and kurtosis, and a given ... -
Approximating Test Statistics Using Eigenvalue Block Averaging
Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2018)We introduce and evaluate a new class of approximations to common test statistics in structural equation modeling. Such test statistics asymptotically follow the distribution of a weighted sum of i.i.d. chi-square variates, ... -
Can children's instructional gameplay activity be used as a predictive indicator of reading skills?
Thomson, Jennifer Marie; Foldnes, Njål; Uppstad, Per Henning; Njå, Morten Bergsten; Solheim, Oddny Judith; Lundetræ, Kjersti (Journal article; Peer reviewed, 2020)For children who may face reading difficulties, early intervention is a societal priority. However, early intervention requires early detection. While much research has approached the issue of identification through measuring ... -
Covariance Model Simulation Using Regular Vines
Grønneberg, Steffen; Foldnes, Njål (Journal article; Peer reviewed, 2017)We propose a new and flexible simulation method for non-normal data with user-specified marginal distributions, covariance matrix and certain bivariate dependencies. The VITA (VIne To Anything) method is based on regular ... -
covsim: An R Package for Simulating Non-normal Data for Structural Equation Models Using Copulas
Grønneberg, Steffen; Foldnes, Njål; Marcoulides, Katerina (Journal article; Peer reviewed, 2022)In factor analysis and structural equation modeling non-normal data simulation is traditionally performed by specifying univariate skewness and kurtosis together with the target covariance matrix. However, this leaves ... -
Developmental Dynamics of Early Reading Skill, Literacy Interest and Reader Self-Concept Within the First Year of Formal Schooling
Walgermo, Bente R.; Foldnes, Njål; Uppstad, Per Henning; Solheim, Oddny Judith (Journal article; Peer reviewed, 2018)Previous studies have documented robust relationships between emergent literacy and later reading performance. A growing body of research has also reported associations between motivational factors and reading in early ... -
Examining the Performance of the Modified ADF Goodness-of-fit Test Statistic in Structural Equation Models
Foldnes, Njål; Marcoulides, George A.; Olsson, Ulf H. (Journal article; Peer reviewed, 2019)The asymptotically distribution-free (ADF) test statistic depends on very mild distributional assumptions and is theoretically superior to many other so-called robust tests available in structural equation modeling. The ... -
Exploring the association between occupational complexity and numeracy
Billington, Mary Genevieve; Foldnes, Njål (Journal article; Peer reviewed, 2021)The basic cognitive skill of numeracy is a recognized form of human capital, associated with economic and social well being for individuals and for nations. In this study, we explore how occupational complexity relates to ... -
Factor analyzing ordinal items requires substantive knowledge of response marginals
Grønneberg, Steffen; Foldnes, Njål (Journal article; Peer reviewed, 2022)In the social sciences, measurement scales often consist of ordinal items and are commonly analyzed using factor analysis. Either data are treated as continuous, or a discretization framework is imposed in order to take ... -
How general is the Vale-Maurelli simulation approach?
Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2015)The Vale-Maurelli (VM) approach to generating non-normal mul- tivariate data involves the use of Fleishman polynomials applied to an underly- ing Gaussian random vector. This method has been extensively used in Monte Carlo ... -
The impact of class attendance on student learning in a flipped classroom
Foldnes, Njål (Peer reviewed; Journal article, 2017)We investigate the relationship between class attendance and academic achievement in a flipped classroom that was designed to foster social learning in fixed groups. Controlling for initial mathematical skill and attitudes, ... -
Non-normal Data Simulation using Piecewise Linear Transforms
Foldnes, Njål; Grønneberg, Steffen (Peer reviewed; Journal article, 2021)We present PLSIM, a new method for generating nonnormal data with a pre-specified covariance matrix that is based on coordinate-wise piecewise linear transformations of standard normal variables. In our presentation, the ... -
On Identification and Non-normal Simulation in Ordinal Covariance and Item Response Models
Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2019)A standard approach for handling ordinal data in covariance analysis such as structural equation modeling is to assume that the data were produced by discretizing a multivariate normal vector. Recently, concern has been ... -
Partial identification of latent correlations with binary data
Grønneberg, Steffen; Moss, Jonas; Foldnes, Njål (Journal article; Peer reviewed, 2020)The tetrachoric correlation is a popular measure of association for binary data and estimates the correlation of an underlying normal latent vector. However, when the underlying vector is not normal, the tetrachoric ... -
Pernicious Polychorics: The Impact and Detection of Underlying Non-normality
Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2019)Ordinal data in social science statistics are often modeled as discretizations of a multivariate normal vector. In contrast to the continuous case, where SEM estimation is also consistent under non-normality, violation of ... -
Residuals and the residual-based statistic for testing goodness of fit of structural equation models
Foldnes, Njål; Foss, Tron; Olsson, Ulf Henning (Journal article; Peer reviewed, 2012)The residuals obtained from tting a structural equation model are crucial ingredients in obtaining chi-square goodness-of- t statistics for the model. We present a didactic discussion of the residuals, obtaining ... -
The sensitivity of structural equation modeling with ordinal data to underlying non-normality and observed distributional forms
Foldnes, Njål; Grønneberg, Steffen (Journal article; Peer reviewed, 2020)Structural equation modeling (SEM) of ordinal data is often performed using normal theory maximum likelihood estimation based on the Pearson correlation (cont-ML) or using least squares principles based on the polychoric ... -
Testing Model Fit by Bootstrap Selection
Grønneberg, Steffen; Foldnes, Njål (Journal article; Peer reviewed, 2018)Over the last few decades, many robust statistics have been proposed in order to assess the fit of structural equation models. To date, however, no clear recommendations have emerged as to which test statistic performs ...