scholarly journals Cross-Product and Cross-Market Adjustments Within Multiproduct Firms: Evidence from Antidumping Actions

2021 ◽  
Author(s):  
Xiaohua Bao ◽  
Bruce Blonigen ◽  
Zhi Yu
Keyword(s):  
Cross Product ◽  
Multiproduct Firms

Acoustical Properties of Speech as Indicators of Depression and Suicidal Risk

2008 ◽  
Vol 4 ◽  
Author(s):  
Michael Joshua Landau
Keyword(s):  
Multiple Regression ◽  
Energy Band ◽  
Mental States ◽  
Cross Product ◽  
Female Group ◽  
Suicidal Risk ◽  
Energy Bands ◽  
Band Ratio ◽  
Acoustical Properties ◽  
Male Group

Acoustical properties of speech have been shown to be related to mental states such as remission and depression. The objective of this project was to relate the energy in frequency bands with the severity of the mental state using the Beck Depression Inventory (BDI). Recorded speech was obtained from male and female subjects with mental states of remission, depression, and suicidal risk. These subjects had recorded automated and spontaneous speech samples. Multiple regression analysis was used to relate the independent energy band ratio variables with the dependent BDI scores, and thus allow the determination of equitable BDI scores for future patients. For the male group, the square of the 3rd energy band and the cross-product of the 2nd and 3rd energy band were prominent in both the reading and interviewed groups. Therefore the equation with the 2nd lowest Akaike Information Criterion (AIC) score was chosen for the reading male group, and the 1st lowest AIC score was chosen for the interviewed male group. For the female group, the square and cross-product of the 1st and 2nd energy bands were prominent in both the reading and interviewed groups. Therefore the 2nd lowest AIC score was chosen for the reading female group, and the 1st lowest AIC score was chosen for the interviewed female group. The clinician could thus determine the patient’s mood or state of mind by comparing the estimated BDI score with the ranges of total BDI scores: remitted 0 – 20, depressed 15 – 38, suicidal 38 – 46. Keywords: speech, mental states, power spectra, multiple regression, information theoretic criterion

scholarly journals Use of the Lagrange Multiplier Test for Assessing Measurement Invariance Under Model Misspecification

2021 ◽  
pp. 001316442110203
Author(s):  
Lucia Guastadisegni ◽  
Silvia Cagnone ◽  
Irini Moustaki ◽  
Vassilis Vasdekis
Keyword(s):  
Lagrange Multiplier ◽  
False Positive ◽  
Latent Variable ◽  
Model Misspecification ◽  
Cross Product ◽  
Small Sample ◽  
Type I ◽  
Local Dependence ◽  
Lagrange Multiplier Test ◽  
Product Approach

This article studies the Type I error, false positive rates, and power of four versions of the Lagrange multiplier test to detect measurement noninvariance in item response theory (IRT) models for binary data under model misspecification. The tests considered are the Lagrange multiplier test computed with the Hessian and cross-product approach, the generalized Lagrange multiplier test and the generalized jackknife score test. The two model misspecifications are those of local dependence among items and nonnormal distribution of the latent variable. The power of the tests is computed in two ways, empirically through Monte Carlo simulation methods and asymptotically, using the asymptotic distribution of each test under the alternative hypothesis. The performance of these tests is evaluated by means of a simulation study. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the tests performance deteriorates, especially for false positive rates under local dependence and power for small sample size under misspecification of the latent variable distribution. In general, the Lagrange multiplier test computed with the Hessian approach and the generalized Lagrange multiplier test have better performance in terms of false positive rates while the Lagrange multiplier test computed with the cross-product approach has the highest power for small sample sizes. The asymptotic power turns out to be a good alternative to the classic empirical power because it is less time consuming. The Lagrange tests studied here have been also applied to a real data set.

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