A comparative evaluation of factor- and component-based structural equation modelling approaches under (in)correct construct representations

Structural equation modelling (SEM) has evolved into two domains, factor-based and component-based, dependent on whether constructs are statistically represented as common factors or components. The two SEM domains are conceptually distinct, each assuming their own population models with either of the statistical construct proxies, and statistical SEM approaches should be used for estimating models whose construct representations correspond to what they assume. However, SEM approaches have often been evaluated and compared only under population factor models, providing misleading conclusions about their relative performance. This is partly because population component models and their relationships have not been clearly formulated. Also, it is of fundamental importance to examine how robust SEM approaches can be to potential misrepresentation of constructs because researchers may often lack clear theories to determine whether a factor or component is more representative of a given construct. Addressing these issues, this study begins by clarifying several population component models and their relationships and then provides a comprehensive evaluation of four SEM approaches – the maximum likelihood approach and factor score regression for factor-based SEM as well as generalized structured component analysis (GSCA) and partial least squares path modelling (PLSPM) for component-based SEM – under various experimental conditions. We confirm that the factor-based SEM approaches should be preferred for estimating factor models, whereas the component-based SEM approaches should be chosen for component models. Importantly, the component-based approaches are generally more robust to construct misrepresentation than the factor-based ones. Of the component-based approaches, GSCA should be chosen over PLSPM, regardless of whether or not constructs are misrepresented.     

Non-Prioritized Ranked Belief Change

Traditional accounts of belief change have been criticized for placing undue emphasis on the new belief provided as input. A recent proposal to address such issues is a framework for non-prioritized belief change based on default theories (Ghose and Goebel, 1998). A novel feature of this approach is the introduction of disbeliefs alongside beliefs which allows for a view of belief contraction as independently useful, instead of just being seen as an intermediate step in the process of belief revision. This approach is, however, restrictive in assuming a linear ordering of reliability on the received inputs. In this paper, we replace the linear ordering with a preference ranking on inputs from which a total preorder on inputs can be induced. This extension brings along with it the problem of dealing with inputs of equal rank. We provide a semantic solution to this problem which contains, as a special case, AGM belief change on closed theories.     

Force and electromyography responses during isometric force release of different rates and step-down magnitudes

This study investigated motor responses of force release during isometric elbow flexion by comparing effects of different ramp durations and step-down magnitudes. Twelve right-handed participants (age: 23.1 ± 1.1) performed trajectory tracking tasks. Participants were instructed to release their force from the reference magnitude (REF; 40% of maximal voluntary contraction force) to a step-down magnitude of 67% REF or 33% REF and maintain the released magnitude. Force release was guided by ramp durations of either 1 s or 5 s. Electromyography of the biceps brachii and triceps brachii was performed during the experimental task, and the co-contraction ratio was evaluated. Force output was recorded to evaluate the parameters of motor performance, such as force variability and overshoot ratio. Although a longer ramp duration of 5 s decreased the force variability and overshoot ratio than did shorter ramp duration of 1 s, higher perceived exertion and co-contraction ratio were followed. Force variability was greater when force was released to the step-down magnitude of 33% REF than that when the magnitude was 67% REF, however, the overshoot ratio showed opposite results. This study provided evidence proving that motor control strategies adopted for force release were affected by both duration and step-down magnitude. In particular, it implies that different control strategies are required according to the level of step-down magnitude with a relatively short ramp duration.     

Option weights should be determined empirically and not by experts when assessing knowledge with multiple‐choice items

Multiple‐choice tests are frequently used in personnel selection contexts to measure knowledge and abilities. Option weighting is an alternative multiple‐choice scoring procedure that awards partial credit for incomplete knowledge reflected in applicants’ distractor choices. We investigated whether option weights should be based on expert judgment or on empirical data when trying to outperform conventional number‐right scoring in terms of reliability and validity. To obtain generalizable results, we used repeated random sub‐sampling validation and found that empirical option weighting, but not expert option weighting, increased the reliability of a knowledge test. Neither option weighting procedure improved test validity. We recommend to improve the reliability of existing ability and knowledge tests used for personnel selection by computing and publishing empirical option weights.     

The Logic of Pragmatic Truth

The mathematical concept of pragmatic truth, first introduced in Mikenberg, da Costa and Chuaqui (1986), has received in the last few years several applications in logic and the philosophy of science. In this paper, we study the logic of pragmatic truth, and show that there are important connections between this logic, modal logic and, in particular, Jaskowski's discussive logic. In order to do so, two systems are put forward so that the notions of pragmatic validity and pragmatic truth can be accommodated. One of the main results of this paper is that the logic of pragmatic truth is paraconsistent. The philosophical import of this result, which justifies the application of pragmatic truth to inconsistent settings, is also discussed.     

Testing for Granger Causality in the Frequency Domain: A Phase Resampling Method

This article introduces phase resampling, an existing but rarely used surrogate data method for making statistical inferences of Granger causality in frequency domain time series analysis. Granger causality testing is essential for establishing causal relations among variables in multivariate dynamic processes. However, testing for Granger causality in the frequency domain is challenging due to the nonlinear relation between frequency domain measures (e.g., partial directed coherence, generalized partial directed coherence) and time domain data. Through a simulation study, we demonstrate that phase resampling is a general and robust method for making statistical inferences even with short time series. With Gaussian data, phase resampling yields satisfactory type I and type II error rates in all but one condition we examine: when a small effect size is combined with an insufficient number of data points. Violations of normality lead to slightly higher error rates but are mostly within acceptable ranges. We illustrate the utility of phase resampling with two empirical examples involving multivariate electroencephalography (EEG) and skin conductance data.     

A logic of comparative obligation

Normal systems of modal logic, interpreted as deontic logics, are unsuitable for a logic of conflicting obligations. By using modal operators based on a more complex semantics, however, we can provide for conflicting obligations, as in [9], which is formally similar to a fragment of the logic of ability later given in [2], Having gone that far, we may find it desirable to be able to express and consider claims about the comparative strengths, or degrees of urgency, of the conflicting obligations under which we stand. This paper, building on the formalism of the logic of ability in [2], provides a complete and decidable system for such a language.     

Taking a closer look: time sampling and measurement error

A person manufactured his in-seat behavior for 15, 30-min sessions so that there were three blocks of five sessions where the behavior occurred 20%, 50%, and 80% of the time. Whole interval, partial interval, and momentary time-sample measures of the behavior were taken and compared to the continuous measure of the behavior i.e., per cent of time the behavior occurred. For interval time sampling, the difference between the continuous and sample measures i.e., measurement error, was: (1) extensive, (2) unidirectional, (3) a function of the time per response, and (4) inconsistent across changes in the continuous measure. A procedural analysis demonstrated that the frequency and duration of behavior are confounded in interval time sampling. Momentary time sampling was found to be superior to interval time sampling in estimating the duration a behavior occurs.     

An evaluation of time-sample measures of behavior

Continuous and time-sample measures of the in-seat behavior of a secretary were obtained. Measurement error, i.e., the extent to which the sample measures deviated from the continuous measure, was a function of the frequency of the sample measurements and the criterion used to score an example of the behavior. If the behavior had to be exhibited throughout the observational interval (whole-interval time sampling), there was a consistent underestimate of the continuous measure. If the behavior had to be exhibited only briefly within the observational interval (partial-interval time sampling), there was a consistent overestimate of the continuous measure. And, if the behavior had to be exhibited at the end of the observational interval (momentary time sampling), overestimations and underestimations of the continuous measure occurred about equally often. As expected, the more frequently the sample measures were made the closer was the agreement between the sample and continuous measures. Two conclusions concerning measurement error in interval time sampling were made. The first was that the error will be a function of the mean time per response. The second is that this error will not be consistent across experimental conditions.