Using Extremes to Design Products and Segment Markets

1995 ◽  
Vol 32 (4) ◽  
pp. 392-403 ◽  
Author(s):  
Greg M. Allenby ◽  
James L. Ginter
Keyword(s):  
Product Design ◽  
Random Effects ◽  
Market Segmentation ◽  
Credit Card ◽  
Hierarchical Bayes ◽  
Random Effects Model ◽  
Product Attributes ◽  
Proposed Model ◽  
Depth Study

Current marketing methodologies used to study consumers are inadequate for identifying and understanding respondents whose preferences for a product offering are most extreme. These “extreme respondents” have important implications for product design and market segmentation decisions. The authors develop a hierarchical Bayes random-effects model and apply it to a conjoint study of credit card attributes. Their proposed model facilitates an in-depth study of respondent heterogeneity, especially of extreme respondents. The authors demonstrate the importance of characterizing extremes in identifying product attributes and predicting the success of potential products.

Adaptive Hierarchical Bayes Estimation of Small Area Proportions

2017 ◽  
Vol 69 (2) ◽  
pp. 150-164 ◽  
Author(s):  
Benmei Liu ◽  
Partha Lahiri
Keyword(s):  
Random Effects ◽  
Small Area ◽  
Probability Distributions ◽  
Random Effect ◽  
Real Data ◽  
Hierarchical Bayes ◽  
Bayes Estimation ◽  
Proposed Model ◽  
Exponential Power ◽  
Power Class

Unit-level logistic regression models with mixed effects have been used for estimating small area proportions in the literature. Normality is commonly assumed for the random effects. Nonetheless, real data often show significant departures from normality assumptions of the random effects. To reduce the risk of model misspecification, we propose an adaptive hierarchical Bayes estimation approach in which the distribution of the random effect is chosen adaptively from the exponential power class of probability distributions. The richness of the exponential power class ensures the robustness of our hierarchical Bayes approach against departure from normality. We demonstrate the robustness of our proposed model using both simulated and real data. The results suggest that the proposed model works reasonably well to incorporate potential kurtosis of the random effects distribution.

Robust bivariate random-effects model for accommodating outlying and influential studies in meta-analysis of diagnostic test accuracy studies

2020 ◽  
Vol 29 (11) ◽  
pp. 3308-3325
Author(s):  
Zelalem F Negeri ◽  
Joseph Beyene
Keyword(s):  
Diagnostic Test ◽  
Random Effects ◽  
Meta Analysis ◽  
Diagnostic Test Accuracy ◽  
Marginal Model ◽  
Test Accuracy ◽  
Random Effects Model ◽  
Random Effects Models ◽  
Proposed Model ◽  
Standard Models

Due to the inevitable inter-study correlation between test sensitivity (Se) and test specificity (Sp), mostly because of threshold variability, hierarchical or bivariate random-effects models are widely used to perform a meta-analysis of diagnostic test accuracy studies. Conventionally, these models assume that the random-effects follow the bivariate normal distribution. However, the inference made using the well-established bivariate random-effects models, when outlying and influential studies are present, may lead to misleading conclusions, since outlying or influential studies can extremely influence parameter estimates due to their disproportional weight. Therefore, we developed a new robust bivariate random-effects model that accommodates outlying and influential observations and gives robust statistical inference by down-weighting the effect of outlying and influential studies. The marginal model and the Monte Carlo expectation-maximization algorithm for our proposed model have been derived. A simulation study has been carried out to validate the proposed method and compare it against the standard methods. Regardless of the parameters varied in our simulations, the proposed model produced robust point estimates of Se and Sp compared to the standard models. Moreover, our proposed model resulted in precise estimates as it yielded the narrowest confidence intervals. The proposed model also generated a similar point and interval estimates of Se and Sp as the standard models when there are no outlying and influential studies. Two published meta-analyses have also been used to illustrate the methods.

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

scholarly journals Updates to the Regional Seismic Travel Time (RSTT) Model: 2. Path-dependent Travel-time Uncertainty

2021 ◽  
Vol 178 (2) ◽  
pp. 313-339
Author(s):  
Michael L. Begnaud ◽  
Dale N. Anderson ◽  
Stephen C. Myers ◽  
Brian Young ◽  
James R. Hipp ◽  
...  
Keyword(s):  
Travel Time ◽  
Random Effects ◽  
Mean Squared Error ◽  
Random Effects Model ◽  
Location Error ◽  
Crust And Upper Mantle ◽  
Time Uncertainty ◽  
Uncertainty Estimates ◽  
Event Location ◽  
Travel Time Uncertainty

AbstractThe regional seismic travel time (RSTT) model and software were developed to improve travel-time prediction accuracy by accounting for three-dimensional crust and upper mantle structure. Travel-time uncertainty estimates are used in the process of associating seismic phases to events and to accurately calculate location uncertainty bounds (i.e. event location error ellipses). We improve on the current distance-dependent uncertainty parameterization for RSTT using a random effects model to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The random effects model separates the error between observed slowness and model predicted slowness into bias and random components. The path-specific travel-time uncertainty is calculated by integrating these mean squared errors along a seismic-phase ray path. We demonstrate that event location error ellipses computed for a 90% coverage ellipse metric (used by the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (IDC)), and using the path-specific travel-time uncertainty approach, are more representative (median 82.5% ellipse percentage) of true location error than error ellipses computed using distance-dependent travel-time uncertainties (median 70.1%). We also demonstrate measurable improvement in location uncertainties using the RSTT method compared to the current station correction approach used at the IDC (median 74.3% coverage ellipse).

Skin Color Matters in the Latinx Community: A Call for Action in Research, Training, and Practice

2021 ◽  
pp. 073998632199591
Author(s):  
Milton A. Fuentes ◽  
Jazmin A. Reyes-Portillo ◽  
Petty Tineo ◽  
Kenny Gonzalez ◽  
Mamona Butt
Keyword(s):  
Cultural Diversity ◽  
Random Effects ◽  
Undergraduate Students ◽  
Skin Color ◽  
Clinical Training ◽  
Research Training ◽  
Random Effects Model ◽  
Concerted Effort ◽  
Training And Research

While skin color is relevant and important in the Latinx community, as it is associated with colorism, little is known about how often it is measured or the best way to measure it. This article presents results from two studies examining these key concerns in three prominent journals, where Latinx research is typically published (i.e., the Hispanic Journal of Behavioral Sciences, the Journal of Latinx Psychology, and Cultural Diversity and Ethnic Minority Psychology). Study one examined whether skin color was measured as a variable, and if so, what measures and methodologies were used. A review of articles ( n = 1,137) showed few studies measured skin color in these three journals, with studies that did so relying on various approaches. Study two aimed to assess the reliability of a widely used skin color measure, the Massey-Martin scale, also known as the New Immigrant Survey (NIS) Skin Scale. Using a sample of 169 undergraduate students, self-ratings, coder ratings, and in vivo ratings were obtained and compared. One-way random effects model analyses indicated excellent reliability with minimal variability across the various ratings. Our findings suggest a critical need to engage in a more concerted effort to assess and discuss the relevance and importance of skin color within the Latinx community. The authors offer some suggestions on how to facilitate these efforts in clinical, training, and research arenas.

scholarly journals Gunshot Wounds to the Lumbosacral Spine: Systematic Review and Meta-Analysis

2021 ◽  
pp. 219256822110308
Author(s):  
Andrew Platt ◽  
Mostafa H. El Dafrawy ◽  
Michael J. Lee ◽  
Martin H. Herman ◽  
Edwin Ramos
Keyword(s):  
Systematic Review ◽  
Random Effects ◽  
Surgical Intervention ◽  
Meta Analysis ◽  
Gunshot Wounds ◽  
Operative Management ◽  
Operative Intervention ◽  
Lumbosacral Spine ◽  
Random Effects Model ◽  
Significant Difference

Study Design: Systematic review and meta-analysis. Objectives: Indications for surgical decompression of gunshot wounds to the lumbosacral spine are controversial and based on limited data. Methods: A systematic review of literature was conducted to identify studies that directly compare neurologic outcomes following operative and non-operative management of gunshot wounds to the lumbosacral spine. Studies were evaluated for degree of neurologic improvement, complications, and antibiotic usage. An odds ratio and 95% confidence interval were calculated for dichotomous outcomes which were then pooled by random-effects model meta-analysis. Results: Five studies were included that met inclusion criteria. The total rate of neurologic improvement was 72.3% following surgical intervention and 61.7% following non-operative intervention. A random-effects model meta-analysis was carried out which failed to show a statistically significant difference in the rate of neurologic improvement between surgical and non-operative intervention (OR 1.07; 95% CI 0.45, 2.53; P = 0.88). In civilian only studies, a random-effects model meta-analysis failed to show a statistically significant difference in the rate of neurologic improvement between surgical and non-operative intervention (OR 0.75; 95% CI 0.21, 2.72; P = 0.66). Meta-analysis further failed to show a statistically significant difference in the rate of neurologic improvement between patients with either complete (OR 4.13; 95% CI 0.55, 30.80; P = 0.17) or incomplete (OR 0.38; 95% CI 0.10, 1.52; P = 0.17) neurologic injuries who underwent surgical and non-operative intervention. There were no significant differences in the number of infections and other complications between patients who underwent surgical and non-operative intervention. Conclusions: There were no statistically significant differences in the rate of neurologic improvement between those who underwent surgical or non-operative intervention. Further research is necessary to determine if surgical intervention for gunshot wounds to the lumbosacral spine, including in the case of retained bullet within the spinal canal, is efficacious.

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