scholarly journals Analyzing data from memory tasks - comparison of ANOVA, logistic regression and mixed logit model

Psihologija ◽  
2018 ◽  
Vol 51 (4) ◽  
pp. 469-488
Author(s):  
Milica Popovic-Stijacic ◽  
Ljiljana Mihic ◽  
Dusica Filipovic-Djurdjevic
Keyword(s):  
Logistic Regression ◽  
Confidence Intervals ◽  
Logit Model ◽  
Linear Models ◽  
Mixed Logit ◽  
Binary Logistic Regression ◽  
Standard Errors ◽  
Parameter Estimates ◽  
Mixed Logit Model ◽  
Mixed Logit Models

We compared three statistical analyses over binary outcomes. As applying ANOVA over proportions violates at least two classical assumptions of linear models, two alternatives are described: the binary logistic regression and the mixed logit model. Firstly, we compared the effects obtained by the three methods over the same data from a previous memory research. All three methods gave similar results: the effects of the tasks and the number of sensory modalities were observed, but not their interaction. Secondly, by using the bootstrap estimates of the parameters, the efficacy of each method was explored. As predicted, the bootstrap parameter estimates of the ANOVA had large bias and standard errors, and consequently wide confidence intervals. On the other hand, the bootstrap parameter estimates of the binary logistic regression and the mixed logit models were similar ? both had low bias and standard errors and narrow confidence intervals.

A Monte Carlo Study of Design Procedures for the Semi-parametric Mixed Logit Model

2016 ◽  
Vol 14 (1) ◽  
Author(s):  
Andreas Falke ◽  
Harald Hruschka
Keyword(s):  
Logit Model ◽  
Linear Models ◽  
Mean Squared Error ◽  
Mixed Logit ◽  
Monte Carlo Study ◽  
Mixed Logit Model ◽  
Design Procedures ◽  
Latent Heterogeneity ◽  
Squared Error ◽  
Minimum Potential

AbstractWe determine efficient designs for choice-based conjoint analysis for the semi-parametric mixed logit model which captures latent consumer heterogeneity in a very flexible way. Different methods constructing one or multiple designs are tested. Additionally we apply Halton draws and determine a minimum potential design for prior draws to reduce computation times caused by accounting for latent heterogeneity of consumers. As main efficiency criteria for the construction of designs we consider measures related to D-error and entropy. As additional benchmarks we generate designs both randomly and by an approach which starts from orthogonal designs developed for linear models. We compare these alternative design procedures by simulating choices for different constellations on the basis of the semi-parametric mixed logit model. Using these simulated choices we estimate parameters of the semi-parametric mixed logit model in the next step. ANOVA with root mean squared error between estimated and true coefficient values as dependent variable shows that performance of design procedures depends on dissimilarity and segment size. Following a mean-standard deviation approach we determine which procedure should be used under different constellations or lack of prior information. Overall, either constructing ten designs based on

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

Modeling head-on crash severity on NCDOT freeways: a mixed logit model approach

2019 ◽  
Vol 46 (4) ◽  
pp. 322-328 ◽  
Author(s):  
Pengfei Liu ◽  
Wei (David) Fan
Keyword(s):  
Logit Model ◽  
Injury Severity ◽  
Safety Information ◽  
Mixed Logit ◽  
Weather Condition ◽  
Mixed Logit Model ◽  
Young Drivers ◽  
Adverse Weather Condition ◽  
Adverse Weather ◽  
Model Approach

This study employs a mixed logit model approach to evaluate contributing factors that significantly affect the severity of head-on crashes. The head-on crash data are collected from Highway Safety Information System (HSIS) from 2005 to 2013 in North Carolina. The effects that vehicle, driver, roadway, and environmental characteristics have on the injury severity of head-on crashes are examined. The results of this research demonstrate that adverse weather, young drivers, rural roadways, and pickups are found to be better modeled as random-parameters at specific injury severity levels, while others should remain fixed. Also, the model results indicate that driving under the influence of alcohol or drugs, grade or curve roadway configuration, old drivers, high speed limit, motorcycles will increase the injury severity of head-on crashes. Adverse weather condition, two-way divided road, traffic control, young drivers, and pickups will decrease the injury severity of head-on crashes.

scholarly journals Using the Econometric Models for Identification of Risk Factors for Albanian Smes (Case Study: Smes of Gjirokastra Region)

2021 ◽  
Vol 18 ◽  
pp. 163-170
Author(s):  
Lorenc Koçiu ◽  
Kledian Kodra
Keyword(s):  
Logistic Regression ◽  
Statistical Models ◽  
Logistic Regression Model ◽  
Qualitative Data ◽  
Linear Models ◽  
Binary Logistic Regression ◽  
Random Variable ◽  
Econometric Models ◽  
Binary Logistic Regression Model

Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sizedEnterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in theGjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likertscale was used to measure it. Finally, the data was processed through statistical software SPSS version 21,using the binary logistic regression model, which reveals the probability of occurrence of an event when allindependent variables are included. Logistic regression is an integral part of a category of statistical models,which are called General Linear Models. Logistic regression is used to analyze problems in which one or moreindependent variables interfere, which influences the dichotomous dependent variable. In such cases, the latteris seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identifyrisks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of thepaper, we conclude that Albanian SMEs can identify risk

Quality and Consumer Choice in Healthcare: Evidence from Kidney Transplantation

2006 ◽  
Vol 5 (1) ◽  
Author(s):  
David H Howard
Keyword(s):  
Kidney Transplantation ◽  
Consumer Choice ◽  
Logit Model ◽  
Mixed Logit ◽  
Mixed Logit Model ◽  
Hospital Level ◽  
Standard Deviation Increase ◽  
Policy Debates ◽  
Medicare Patients ◽  
Insured Patients

AbstractMost studies of competition in health care focus on prices and costs, but concerns about quality play a central role in policy debates. If demand is inelastic to quality, then competition may reduce patient welfare. This study uses a dataset of patient registrations for kidney transplantation in conjunction with a mixed logit model to gauge consumers’ responsiveness to quality when choosing hospitals. Results indicate that at the hospital level, a one-standard deviation increase in the graft-failure rate is associated with a 6% decline in patient registrations. Privately-insured patients are more responsive to quality than Medicare patients, suggesting that insurers consider quality when contracting with providers.

scholarly journals Economic Valuation of Local Environmental Amenities: A Case Study of Bahir Dar City, Amhara Regional State, Ethiopia

2021 ◽  
pp. 698-711
Author(s):  
Mekuannet Worku ◽  
Tefera Berihun Taw ◽  
Malaku Tarekegn
Keyword(s):  
Logit Model ◽  
Mixed Logit ◽  
Sampling Technique ◽  
Preference Heterogeneity ◽  
Primary Data ◽  
Mixed Logit Model ◽  
Palm Tree ◽  
Bahir Dar ◽  
Environmental Amenities ◽  
Attribute Levels

This study estimates the economic value of local environmental amenities in Bahir Dar city which is one of the tourist attraction sites in Ethiopia. The study employed choice experiment valuation method by identifying four environmental amenities attributes (Lake Tana, urban park, palm tree and street cleanliness). The study used probability multi-stage random sampling technique. The analysis was based on primary data surveyed from households in Bahir Dar city. The study presented nine choices set for each respondent; each choice set has three alternatives including the status quo option. The study employed a mixed logit model. The result showed that all improved attribute levels have positive signs and statistically significant. As expected and consistent with economic theory the monetary cost has negative signs and significant. The mixed logit model showed that there is preference heterogeneity in some attribute levels. Based on the finding, the study recommends that the city administration and the concerned body expected to implement the hypothetical policy scenario so as to improve environmental amenity.

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