Prediction in HRM research–A gap between rhetoric and reality

There are broadly two dimensions on which researchers can evaluate their statistical models: explanatory power and predictive power. Using data on job satisfaction in ageing workforces, we empirically highlight the importance of distinguishing between these two dimensions clearly by showing that a model with a certain degree of explanatory power can produce vastly different levels of predictive power and vice versa—in the same and different contexts. In a further step, we review all the papers published in three top-tier human resource management journals between 2014 and 2018 to show that researchers generally confuse explanation and prediction. Specifically, while almost all authors rely solely on explanatory power assessments (i.e., assessing whether the coefficients are significant and in the hypothesised direction), they also derive practical recommendations, which inherently result from a predictive scenario. Based on our results, we provide HRM researchers recommendations on how to improve the rigour of their explanatory studies

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM

A Pair of Compact Red Galaxies at Redshift 2.38, Immersed in a 100 kpc Scale Ly-alpha Nebula

We present Hubble Space Telescope (HST) and ground-based observations of a pair of galaxies at redshift 2.38, which are collectively known as 2142-4420 B1 (Francis et al. 1996). The two galaxies are both luminous extremely red objects (EROs), separated by 0.8 arcsec. They are embedded within a 100 kpc scale diffuse Ly-alpha nebula (or blob) of luminosity ~10^44 erg/s. The radial profiles and colors of both red objects are most naturally explained if they are young elliptical galaxies: the most distant yet found. It is not, however, possible to rule out a model in which they are abnormally compact, extremely dusty starbursting disk galaxies. If they are elliptical galaxies, their stellar populations have inferred masses of ~10^11 solar masses and ages of ~7x10^8 years. Both galaxies have color gradients: their centers are significantly bluer than their outer regions. The surface brightness of both galaxies is roughly an order of magnitude greater than would be predicted by the Kormendy relation. A chain of diffuse star formation extending 1 arcsec from the galaxies may be evidence that they are interacting or merging. The Ly-alpha nebula surrounding the galaxies shows apparent velocity substructure of amplitude ~ 700 km/s. We propose that the Ly-alpha emission from this nebula may be produced by fast shocks, powered either by a galactic superwind or by the release of gravitational potential energy.Comment: 33 pages, 9 figures, ApJ in press (to appear in Jun 10 issue

Stimulation of osteoclast formation by inflammatory synovial fluid. Virchows Arch. 449: 69–77

Abstract Peri-articular bone resorption is a feature of arthritis due to crystal deposition and rheumatoid disease. Under these conditions, the synovial fluid contains numerous inflammatory cells that produce cytokines and growth factors which promote osteoclast formation. The aim of this study was to determine whether inflammatory synovial fluid stimulates the formation of osteoclasts. Synovial fluid from rheumatoid arthritis (RA), pyrophosphate arthropathy (PPA) and osteoarthritis (OA) patients was added to cultures (n=8) of human peripheral blood mononuclear cells (PBMCs) in the presence and absence of macrophage colony-stimulating factor (M-CSF) and the receptor activator of NF-κB ligand (RANKL). Osteoclast formation was assessed by the formation of cells positive for tartrate-resistant acid phosphatase (TRAP) and vitronectin receptor (VNR) and the extent of lacunar resorption. The addition of 10% OA, RA and PPA synovial fluid to PBMC cultures resulted in the formation of numerous multinucleated or mononuclear TRAP + and VNR + cells which were capable of lacunar resorption. In contrast to PBMC cultures incubated with OA synovial fluid, there was marked stimulation of osteoclast formation and resorption in cultures containing inflammatory RA and PPA synovial fluid which contained high levels of tumour necrosis factor alpha, a factor which is known to stimulate RANKL-induced osteoclast formation

Stimulation of osteoclast formation by inflammatory synovial fluid

Peri-articular bone resorption is a feature of arthritis due to crystal deposition and rheumatoid disease. Under these conditions, the synovial fluid contains numerous inflammatory cells that produced cytokines and growth factors which promote osteoclast formation. The aim of the study was to determine whether inflammatory synovial fluid stimulates the formation of osteoclasts. Synovial fluid from rheumatoid arthritis (RA), pyrophosphate arthropathy (PPA) and osteoarthritis (OA) patients was added to cultures (n=8) of human peripheral blood mononuclear cells (PBMCs) in the presence and absence of macrophage colony-stimulating factor (M-CSF) and the receptor activator of NF-KB ligand (RANKL). Osteoclast formation was assessed by the formation of cells positive for tartrare-resistant and phosphatase (TRAP) and vitronectin receptor (VNR) and the extent of lacunar resorption. The addition of 10% OA, RA and PPA synovial fluid to PBMC cultures resulted in the formation of numerous multinicleated or mononuclear TRAP⁺ and VNR⁺ cells which were capable of lacunar resorption. In contrast to PBMC cultures incubated with OA synovial fluid, there was marked stimulation of osteoclast formation and resorption in cultures containing inflammatory RA and PPA synovial fluid which contained high levels of tumour necrosis factor alpha, a factor which is known to stimulate RANKL-induced osteoclast formation

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM