Empirical Logit Research Articles

A New Partial Correlation Coefficient Technique Based on Intuitionistic Fuzzy Information and Its Pattern Recognition Application

Computation of correlation coefficient among attributes of ordinary database is important especially in the classification and analysis of data. Due to the hesitations in the process of data classification, the idea of intuitionistic fuzzy data (IFD) is appropriate for a reliable classification. To achieve a dependable correlation, the construct of partial correlation coefficient based on IFD has been considered. The construct of partial correlation coefficient of intuitionistic fuzzy sets (PCCIFSs) is reasonable since correlation coefficients of intuitionistic fuzzy sets (CCIFSs) are limited in the sense that it only expressed linear association and direction of such relation between IFD without minding the effect of other IFD. On the contrary, partial correlation coefficient finds the exact association between any two IFD by muting the effect of other IFD which could sway the result of the correlation coefficient. In previous works, the idea of PCCIFSs was introduced based on the multivariate correlation model using empirical logit transform. Besides the fact that the outputs of multivariate correlation model are not always easy to interpret, the approach also never considered the three parameters of IFSs and does not use the values of CCIFSs for the computational process. With these setbacks, we are motivated to propose a novel approach of finding PCCIFSs by incorporating the three parameters of IFD based on a modified CCIFSs approach. A comparative analysis of the robust PCCIFSs approach and the existing approach is considered to justify the novel approach. An application of the new approach of PCCIFSs is considered in the case of pattern recognition where the patterns are represented as intuitionistic fuzzy data.

Evaluating empirical evidence for housing development effects on the management of remaining private-owned forest in the U.S.

Forest ecosystems are notably influenced by: 1) the rate and spatial distribution of forest land development, and 2) how remaining undeveloped forest lands are managed. Regarding this second factor, economics and ecology research conducted in different locations in the U.S. suggests that increasing housing development can reduce the profitability of commercial timber production and thus the intensity with which landowners manage their forest lands. Some studies, however, suggest that in some locations these effects are not evident. We sought to consider what contextual factors might influence where and when development effects on forest management might become evident. We began with a critical review and synthesis of existing research addressing the degree to which housing development influences private forest management. We followed that with an empirical (logit) analysis of the likelihood of “active” (e.g., thinning) and extractive (e.g., harvesting) management on nonindustrial private forest lands in Oregon and Washington (U.S.), as a function of stand, site, and other factors, including nearby housing development. From our review and synthesis of previous research literature, we conclude that the varying results of previous studies likely owe to a combination of biophysical and socioeconomic contextual factors that influence both how prevalent development impacts might be in different locations and how easily they can be observed in empirical analyses. The results of our analysis of active and extractive management in Oregon and Washington are largely consistent with this finding, with some regions showing statistically significant negative effects owing to housing development, and other regions remaining largely unaffected. We conclude that policymakers and managers need to consider the biophysical and socioeconomic context of different study areas when evaluating the implications of individual study results.

The Welfare Effects of Spotify’s Cross-Country Price Discrimination

We calibrate a simple empirical logit model of world demand—and subscription pricing—at Spotify, with the use of available data on monthly prices and using streaming volumes by country to create measures of the numbers of users. We find that country-specific pricing increases revenue by 5.9% relative to uniform world pricing, while country specific pricing decreases world consumer surplus by 1.0%. Country-specific pricing within Europe increases revenue in Europe by 1.1%, and EU consumer surplus increases by 0.3% with country-specific pricing. Consumers in lower-income countries gain more from price discrimination than do the consumers in higher-income countries.

Real-time social reasoning: the effect of disfluency on the meaning of some

The scalar quantifier some is locally ambiguous between pragmatic (some-but-not-all) and literal (some-and-possibly-all) meanings. Although comprehenders typically favour an eventual pragmatic interpretation, debate persists regarding what factors influence interpretation, the time course of comprehension, and whether literal meaning takes precedence. We investigate how the interpretation of some depends on social reasoning derived from a speaker’s manner of delivery. Specifically, we test the effect of disfluency on the derivation of meaning in a context where hesitation may signal speaker embarrassment due to potential face-loss associated with the literal meaning of “some”. Participants (n=24) viewed displays comprising two different snack quantities while hearing a recorded utterance describing how much a speaker had eaten. Critical utterances (n=16) contained the quantifier some, half with a filled pause disfluency (“I ate <uh>, some oreos”). Participants’ eye and mouse movements showed (via empirical logit regressions) that fluent utterances yielded a bias toward a pragmatic interpretation, while disfluency attenuated this bias in favour of the literal meaning (where the speaker ate all the oreos). Crucially, this difference emerged rapidly post-onset of some. Taken together, our findings do not support a literal-first account of scalar comprehension, but rather, suggest that some is interpreted rapidly in a context-dependent manner.

Empirical logit analysis is not logistic regression

Abstract Many recent psycholinguistic studies have used empirical logit analysis as a substitute for mixed-effects logistic regression. In this paper, we describe the differences between empirical logit analysis and mixed-effects logistic regression and highlight three interacting sources of bias in empirical logit analysis. We then report on two sets of simulations comparing logistic regression and empirical logit analysis. We show that relative to logistic regression, empirical logit analysis generally yields biased parameter estimates when proportions are close to 0 or 1, especially when the number of observations underlying a proportion is very low. We also show that, in some circumstances, this bias can create spurious interactions, leading to unacceptable Type I error rates. While these two models may provide similar answers to some questions, we encourage readers to interpret empirical logit parameters cautiously.

Use of two-part regression calibration model to correct for measurement error in episodically consumed foods in a single-replicate study design: EPIC case study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Living Arrangement Preferences of Elderly People in Taiwan as Affected by Family Resources and Social Participation

This article investigates living arrangement preferences of elderly people in Taiwan, including coresidence with family (their children or spouse), coresidence with spouse only, living alone, and living in an institution. The authors consider the effects of three factors: the elderly persons’ health situation, their family resources, and their social participation, such as community workshops or political activities. Accordingly, the authors propose empirical logit models based on the well-developed discrete choice theory. Empirical results reveal that (1) elderly people with higher socioeconomic status, prefer either independent living arrangements or coresidence with their children, (2) elderly people with more family resources, such as large family size, prefer to coreside with their children, and (3) elderly people with adequate social support and/or contact networks prefer independent living arrangements.

Chemical Use Reductions in Urban Fringe Agriculture

Using an augmented profit function framework designed to account for externalities related to chemical use in agriculture, this paper explains the chemical use choices of farmers in an urban fringe farming environment. It further estimates empirical logit models of reduced insecticide, fungicide, herbicide, and fertilizer usage. Results suggest that farmers who perceive their regulatory environment to be strict, who have experienced right-to-farm conflicts, and who have farms larger in size are more likely to reduce their chemical use over time, vis-à-vis other farmers. The results also suggest the importance of other farm structural and business climate factors in determining chemical use reduction choices.

Abandoning Non-State Allies: Not a Matter of Strategy

Generation of effective counterinsurgency and counterterrorism techniques has been placed at the top of the scholarly agenda in the aftermath of September 11. Dissuading state support of terrorist groups and insurgency movements is one of the vital components of an effective counterinsurgency or counterterrorism techniques. While the scholars have been motivated by exploring the micro-level determinants of insurgency and terrorism, since they thought that it is the key to deal with insurgent and terrorist violence in the long run, they have long undermined the role of “state” on the generation and endurance of insurgency and terrorist movements. Nevertheless, it is essential to distinguish between the conditions that lead states to support such groups as a foreign policy instrument and those that make them abandon these groups. I argue that although states are motivated by strategic and ideational interests in initiating their support of certain groups, the termination of support is driven by rather practical and imminent concerns. States are more likely to terminate their support of a group if they realize that it poses a threat to domestic stability and survival of leaders. In addition, there are multiple modes of support termination, target pressures, international pressures, leadership or regime change in the supporter, groups’ change of their supporters, and target-supporter coordination. Each is driven by different factors. Two sets of empirical analyses, multinomial logit and Cox proportional hazard analyses have been conducted on original data collected for the period between 1945 and 2001. The findings support the arguments with respect to imminent gains and the presence of multiple modes of termination.

Institutional Choices for Local Service Contracting and Collaboration

Outsourcing local services necessitates collaborative relationships, yet we know little about local service delivery mechanism choices that formalize these relationships. Alternatives to in-house production include contracts with for-profit organizations, provision by local authorities, and intergovernmental agreements. Previous studies of service choices focus on potential “efficiency gains” from external exchange, especially the economic costs on the supplier’s side resulting from market failure or asset specificities. This study instead applies the political market framework to examine how collaborative local service arrangements are shaped by or respond to supply and demand characteristics. The empirical analysis estimates, logit and multinomial probit models of public service delivery in Georgia. Ferris and Graddy (1986) suggest that decisions reflect a two-step process, i.e., choosing whether or not to contract out and then choosing with whom to contract. This paper also follows their two-step approach. Each local government decides whether or not to collaborate (logit model) and then chooses with whom to collaborate (multinomial probit model). The findings indicate that the transaction cost of supply and demand factors defined by the political market framework affect the choices of collaborative arrangements and alternative service delivery mechanisms.

Testing for Misspecification in Binary Response Models with Competing Distributions

In empirical studies, the probit and logit models are often used without checks for their competing distributional specifications. It is also rare for econometric tests to be focused on this issue. Santos Silva [Journal of Applied Econometrics (2001), Vol. 16, pp. 577–597] is an important recent exception. By using the conditional moment test principle, we discuss a wide class of non‐nested tests that can easily be applied to detect the competing distributions for the binary response models. This class of tests includes the test of Santos Silva (2001) for the same task as a particular example and provides other useful alternatives. We also compare the performance of these tests by a Monte Carlo simulation.

Global endemicity centres for terrestrial vertebrates: an ecoregions approach

Endemic taxa are those restricted to a specific area, and can be defined as the exclusive biodiversity of a region. Areas with high endemic numbers are irreplaceable, and are of high priority for conservation. We investigated global patterns of endemicity of terrestrial vertebrates (mammals, birds, reptiles and amphibians) by employing data from World Wildlife Fund-US on 26 452 species distributions (endemic and non-endemic) within 796 ecoregions. Ecoregions represent global ecosys- tem and habitat types at a landscape level. We explored the entire dataset by first using a principal components analysis, PCA, to identify which parameters and ordinations (transformations) best char- acterise the ecoregions. PCA identified the empirical logit transformation of proportional endemicity, not absolute or relative endemicity, as the appropriate variable. We prioritised ecoregions by ranking the empirical logit transformation of proportional endemicity, standardised across animal groups to avoid taxonomic biases. Finally, we analysed how ecoregion characteristics and the degree of isola- tion correlated with endemicity in all studied groups, by fitting logistic regression models. We argue that using our method, conservationists can better denote areas of importance for protection of endemic biodiversity worldwide.

Multiple and Partial Correlation Coefficients of Fuzzy Sets

In many applications, multiple correlation and partial correlation for three or more fuzzy sets are very important, but Chiang and Lin (1999, Fuzzy Sets and Systems 102: 221–226) do not solve this problem. Here, we propose a method to calculate the multiple correlation and partial correlation for fuzzy data, by adopting the concepts from the multivariate correlation model. In order to fit into normal framework, we use empirical logit transform (see, Agresti, [1990, Categorical Data Analysis. New York: Wiley]; Johnson and Wichern, [1992, Applied Multivariate Statistical Analysis 3rd edn. Engelwood Cliffs; Prentice-Hall.]) for membership function grades to achieve this.

Modeling the interaction of parties, activists and voters: Why is the political center so empty?

Abstract. The formal stochastic model of voting should be the theoretical benchmark against which empirical models can be gauged. A standard result in the formal model is the ‘mean voter theorem’ stating that parties converge to the electoral center. Empirical analysis based on the vote‐maximizing premise, however, invalidates this convergence result. We consider both empirical and formal models that incorporate exogeneous valence terms for the parties. Valence can be regarded as an electorally perceived attribute of each party leader that is independent of the policy position of the party. We show that the mean voter theorem is valid for empirical multinomial logit and probit models of a number of elections in the Netherlands and Britain. To account for the non‐centrist policy positions of parties, we consider a more general formal model where valence is also affected by the behavior of party activists. The results suggest that non‐convergent policy choice by party leaders can be understood as rational, vote‐maximizing calculation by leaders in response to electoral and activist motivations.

PARTIAL CORRELATION COEFFICIENTS OF INTUITIONISTIC FUZZY SETS

In many applications, partial correlation for three or more intuitionistic fuzzy sets are very important, but Hung [12] do not discuss this problem. In this paper, we propose a method to calculate the partial correlation of intuitionistic fuzzy sets by means of multivariate correlation model. In order to fit into normal framework, we use empirical logit transform (see Agresti [1] and Johnson and Wichern [13]) for the degree of membership of intuitionistic fuzzy set to achive this.

Neural Network for Gap Acceptance at Stop‐Controlled Intersections

The behavior of gap acceptance by vehicles at intersections with stop signs involves the complex interaction of numerous geometric, traffic, and environmental factors. Several methods, including empirical analysis, and theoretical, logit, and probit models have been used to estimate gap acceptance at stop‐controlled intersections. In the past, neural networks have been used to examine problems involving complex interrelationship among many variables and found to perform better than conventional methods. This paper describes the development of a neural network and a binary‐logit model for predicting accepted or rejected gaps at rural, low‐volume two‐way stop‐controlled intersections. The type of control, the turning movements in both the major and minor directions, size of gap, service time, stop type, vehicular speed, queue in the minor direction, and existence of vehicle in the opposite approach were found to influence the driver's decision to accept or reject a gap. The results of the neural network and...

Heritability estimates of pregnancy rate in beef cows under natural mating.

Observations of 3,029 matings over 17 yr on an Ozark upland range were used to estimate heritability of pregnancy rate in Angus, Hereford and Polled Hereford cows. Pregnancy rate, the percentage of cows exposed that produced a live calf in the spring, was transformed using the empirical logit transformation and then analyzed for each breed separately by weighted least squares using a mixed model procedure. A numerator relationship matrix for sires of cows was incorporated into the sire model to account for relationships among sires. Variation among years significantly affected pregnancy rate in all three breeds. Age of dam significantly affected pregnancy rate in the Angus and Hereford groups. Paternal half-sib estimates of heritability from the observed binary data (h2b) for pregnancy rate were calculated on first-calf heifers and mature cows for each breed. Respective h2b estimates for heifers and mature cows were .17 and .09 in the Angus group, .04 and .01 in the Hereford group and .05 and .05 in the Polled Hereford group. The heritability estimates when binary records were transformed to the probit scale (h2) were .04 +/- .003 and .02 +/- .001 for Angus, .01 +/- .002 and 0 for Hereford and .01 +/- .001 and .02 +/- .001 for Polled Hereford for heifers and mature cows, respectively. Heritability estimates in this study are in agreement with the literature, indicating little opportunity for improvement in pregnancy rate by selection within a breed.

Factors in the adoption of industial development incentives by states

The continued proliferation of state indusrial development incentive programmes in the absence of any evidence of their effectiveness raises several interesting policy questions. First, why do states continue to adopt new incentive programmes and secondly, what factors determine the type of new incentives that are adopted? These questions are investigated through the use of a set of empirical (logit) models of states' decisions to adopt new industrial development incentive programmes. In these models the decisions are hypothesized to be influenced by the states's economic and fiscal condition, the state's relative advantages and disadvantages with respect to important industrial location factors, and the incentive packages of the subject state and its neighbours. The results provide limited support for the frequently advanced, but previously untested, hypothesis that a primary determinant of a state's incentive adoption decision is the recent adoption of similar incentivies in neighbouring states. The dec...

A comparison of estimators of the degree of insect control

The current estimator of the degree of insect control by an insecticide in a field experiment laid out in randomized blocks is equal to one minus the cross-product ratio of a two way table of total insect counts over blocks. Since much work has been done on estimation of the common odds ratio of a number of strata in medical studies, a series of Monte Carlo studies was performed to investigate the possible use of these estimators and their standard errors in estimating the common degree of inject control of a number of blocks. Maximum likelihood, Mantel-Haenszel, and empirical logit estimators were evaluated and compared with back-transformed means over blocks, of cross-product ratios on the arithmetic, logarithmic, and arcsine scales. Maximum likelihood and Mantel-Haenszel estimators had the smallest mean squared errors, but their standard error estimates were only appropriate when sampling distributions were approximately Poisson and there was little heterogeneity among plots within blocks in the natura...

Further results on the effect of bias, variance estimation, and non-normality of the empirical logit on weighted least squares analyses

(1986). Further results on the effect of bias, variance estimation, and non-normality of the empirical logit on weighted least squares analyses. Communications in Statistics - Theory and Methods: Vol. 15, No. 3, pp. 755-782.