Does Sparseness Matter? Examining the Use of Generalizability Theory and Many-Facet Rasch Measurement in Sparse Rating Designs.

Sparse rating designs, where each examinee's performance is scored by a small proportion of raters, are prevalent in practical performance assessments. However, relatively little research has focused on the degree to which different analytic techniques alert researchers to rater effects in such designs. We used a simulation study to compare the information provided by two popular approaches: Generalizability theory (G theory) and Many-Facet Rasch (MFR) measurement.

Interrogating the Mechanistic Features of Ni(I)-Mediated Aryl Iodide Oxidative Addition Using Electroanalytical and Statistical Modeling Techniques.

While the oxidative addition of Ni(I) to aryl iodides has been commonly proposed in catalytic methods, an in-depth mechanistic understanding of this fundamental process is still lacking. Herein, we describe a detailed mechanistic study of the oxidative addition process using electroanalytical and statistical modeling techniques. Electroanalytical techniques allowed rapid measurement of the oxidative addition rates for a diverse set of aryl iodide substrates and four classes of catalytically relevant complexes (Ni(BPy), Ni(Phen), Ni(Terpy), and Ni(BPP)).

Investigating Oxidative Addition Mechanisms of Allylic Electrophiles with Low-Valent Ni/Co Catalysts Using Electroanalytical and Data Science Techniques.

The catalysis by a π-allyl-Co/Ni complex has drawn significant attention recently due to its distinct reactivity in reductive Co/Ni-catalyzed allylation reactions. Despite significant success in reaction development, the critical oxidative addition mechanism to form the π-allyl-Co/Ni complex remains unclear. Herein, we present a study to investigate this process with four catalysis-relevant complexes: Co(BPy)Br, Co(Phen)Br, Ni(BPy)Br, and Ni(Phen)Br.

The Stabilizing Influences of Linking Set Size and Model-Data Fit in Sparse Rater-Mediated Assessment Networks.

Previous research includes frequent admonitions regarding the importance of establishing connectivity in data collection designs prior to the application of Rasch models. However, details regarding the influence of characteristics of the linking sets used to establish connections among facets, such as locations on the latent variable, model-data fit, and sample size, have not been thoroughly explored. These considerations are particularly important in assessment systems that involve large proportions of missing data (i.

Using Repeated Ratings to Improve Measurement Precision in Incomplete Rating Designs.

When selecting a design for rater-mediated assessments, one important consideration is the number of raters who rate each examinee. In balancing costs and rater-coverage, rating designs are often implemented wherein only a portion of the examinees are rated by each judge, resulting in large amounts of missing data. One drawback to these sparse rating designs is the reduced precision of examinee ability estimates they provide.

The attenuating effect of role overload on relationships linking self-efficacy and goal level to work performance.

The reported research examines the moderating effects of role overload on the antecedents and consequences of self-efficacy and personal goal level in a longitudinal study conducted in an industrial selling context. The results indicate that role overload moderates the antecedent effect of perceived organizational resources on self-efficacy beliefs. They also show that role overload moderates the direct effects of both self-efficacy and goal level on performance, such that these relationships are positive when role overload is low but not significant when role overload is high.