Purpose: The aim of this study is to examine the mediating role loneliness between internet addictions accountants with their burnout levels. Methodology: Using survey method, 231 responses were solicited from in Turkiye. A partial least squares structural equation model was constructed order test both reliability and validity measurement, as well model. Findings: results indicated that partial...

Partial least squares modeling as a powerful multivariate statistical tool was applied tothe simultaneous spectrophotometric determination of silicate and phosphate in aqueoussolutions. The concentration range for silicate and phosphate were 0.02-0.6 and 0.4-3 μg ml-1,respectively. The experimental calibration set was composed with 30 sample solutions using amixture design for two component mix...

BACKGROUND In this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit 'Calrico' (n = 260) to predict Magness-Taylor (MT) firmness. METHODS Separate and combined use of these measures was evaluated and compared using partial least squares (PLS) and least squares support vector machine (LS-SVM) regression met...

Composite-based methods like partial least squares (PLS) path modeling have an advantage over factor-based methods (like CB-SEM) because they yield determinate predictions, while factor-based methods’ prediction is constrained in this regard by factor indeterminacy. To maximize practical relevance, research findings should extend beyond the study’s own data. We explain how PLS practices, derivi...

Principal components analysis is traditionally presented as an interpretive multivariate technique, where the loadings are chosen to maximally explain the variance in the variable. However, we will consider it here mainly as a statistical learning tool, by using the derived components in a least squares regression to predict unobserved response variables using the principal components. Principa...

With an increasing number of publicly available microarray datasets, it becomes attractive to borrow information from other relevant studies to have more reliable and powerful analysis of a given dataset. We do not assume that subjects in the current study and other relevant studies are drawn from the same population as assumed by meta-analysis. In particular, the set of parameters in the curre...

Partial Least Squares (PLS) is a statistical technique that is widely used in the Information Systems discipline to estimate statistical models with structural equations and latent variables. While PLS does not provide a statistical test of model fit to data, its proponents have suggested a set of criteria that good PLS models should fulfill. Conversely, when a model does not satisfy these crit...

Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess di...