Regression Models for Count Data in R Zeileis, Achim; Kleiber, Christian; Jackman, Simon
Journal of statistical software,
2008, Letnik:
27, Številka:
8
Journal Article
Recenzirano
Odprti dostop
The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in ...the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inflated regression models in the functions hurdle() and zeroinfl() from the package pscl is introduced. It re-uses design and functionality of the basic R functions just as the underlying conceptual tools extend the classical models. Both hurdle and zero-inflated model, are able to incorporate over-dispersion and excess zeros-two problems that typically occur in count data sets in economics and the social sciences—better than their classical counterparts. Using cross-section data on the demand for medical care, it is illustrated how the classical as well as the zero-augmented models can be fitted, inspected and tested in practice.
Employing a comparative experimental design drawing on over 18,000 interviews across eleven countries on four continents, this article revisits the discussion about the economic and cultural drivers ...of attitudes towards immigrants in advanced democracies. Experiments manipulate the occupational status, skin tone and national origin of immigrants in short vignettes. The results are most consistent with a Sociotropic Economic Threat thesis: In all countries, higher-skilled immigrants are preferred to their lower-skilled counterparts at all levels of native socio-economic status (SES). There is little support for the Labor Market Competition hypothesis, since respondents are not more opposed to immigrants in their own SES stratum. While skin tone itself has little effect in any country, immigrants from Muslim-majority countries do elicit significantly lower levels of support, and racial animus remains a powerful force.
The Statistical Analysis of Roll Call Data CLINTON, JOSHUA; JACKMAN, SIMON; RIVERS, DOUGLAS
The American political science review,
05/2004, Letnik:
98, Številka:
2
Journal Article
Recenzirano
Odprti dostop
We develop a Bayesian procedure for estimation and inference for spatial models of roll call voting. This approach is extremely flexible, applicable to any legislative setting, irrespective of size, ...the extremism of the legislators' voting histories, or the number of roll calls available for analysis. The model is easily extended to let other sources of information inform the analysis of roll call data, such as the number and nature of the underlying dimensions, the presence of party whipping, the determinants of legislator preferences, and the evolution of the legislative agenda; this is especially helpful since generally it is inappropriate to use estimates of extant methods (usually generated under assumptions of sincere voting) to test models embodying alternate assumptions (e.g., log-rolling, party discipline). A Bayesian approach also provides a coherent framework for estimation and inference with roll call data that eludes extant methods; moreover, via Bayesian simulation methods, it is straightforward to generate uncertainty assessments or hypothesis tests concerning any auxiliary quantity of interest or to formally compare models. In a series of examples we show how our method is easily extended to accommodate theoretically interesting models of legislative behavior. Our goal is to provide a statistical framework for combining the measurement of legislative preferences with tests of models of legislative behavior.
Bayesian statistics have made great strides in recent years, developing a class of methods for estimation and inference via stochastic simulation known as Markov Chain Monte Carlo (MCMC) methods. ...MCMC constitutes a revolution in statistical practice with effects beginning to be felt in the social sciences: models long consigned to the "too hard" basket are now within reach of quantitative researchers. I review the statistical pedigree of MCMC and the underlying statistical concepts. I demonstrate some of the strengths and weaknesses of MCMC and offer practical suggestions for using MCMC in social-science settings. Simple, illustrative examples include a probit model of voter turnout and a linear regression for time-series data with autoregressive disturbances. I conclude with a more challenging application, a multinomial probit model, to showcase the power of MCMC methods.
Pooling the polls over an election campaign Jackman, Simon
Australian journal of political science,
12/1/2005, 20051201, 2005-12-00, Letnik:
40, Številka:
4
Journal Article
Recenzirano
Poll results vary over the course of a campaign election and across polling organisations, making it difficult to track genuine changes in voter support. I present a statistical model that tracks ...changes in voter support over time by pooling the polls, and corrects for variation across polling organisations due to biases known as 'house effects'. The result is a less biased and more precise estimate of vote intentions than is possible from any one poll alone. I use five series of polls fielded over the 2004 Australian federal election campaign (ACNielsen, the ANU/ninemsn online poll, Galaxy, Newspoll, and Roy Morgan) to generate daily estimates of the Coalition's share of two-party preferred (2PP) and first preference vote intentions. Over the course of the campaign there is about a 4 percentage point swing to the Coalition in first preference vote share (and a smaller swing in 2PP terms), that begins prior to the formal announcement of the election, but is complete shortly after the leader debates. The ANU/ninemsn online poll and Morgan are found to have large and statistically significant biases, while, generally, the three phone polls have small and/or statistically insignificant biases, with ACNielsen and (in particular) Galaxy performing quite well in 2004.
* An earlier version of this paper was prepared for the annual meeting of the Australasian Political Studies Association, University of Adelaide, 29 September-1 October 2004.
The use of nano-scale particles as a means of environmental remediation still provides a comparatively novel approach for the treatment of contaminated waters. The current study compares the ...reactivity of micro-scale Fe, nano-scale Fe and nano-scale Ni/Fe (nickel/iron) particles specifically for dechlorination of solutions containing 350
mg
L
−1 of TCE (concentration measured at a contaminated site in Derbyshire, UK). The results indicated that employing 1
g
L
−1 of reactive material for dechlorination in the monometallic form (both micro- and nano-scale) exhibited very little reduction capability compared with the bimetallic Ni/Fe nano-scale particles, containing 28.9% Ni (in molar), which achieved complete dechlorination of the TCE in solution within 576
h. Experiments were also performed to determine the optimum bimetallic composition of the Ni/Fe particles for TCE reduction. This revealed that 3.2% Ni was the optimum Ni/Fe molar ratio for both maximum dehalogenation performance and minimum release of Ni into solution. Using particles of the most effective bimetallic composition, experiments were carried out to determine the concentration required for optimal TCE reduction. Over the range of nano-scale particle concentrations tested (0.1–9
g
L
−1), reduction rates of TCE increased with greater TCE:nano-scale particle ratios. However, a concentration range of 1–3
g
L
−1 was selected as the most appropriate for site remediation, since more concentrated solutions demonstrated only small increases in rates of reaction. Finally, in order to test the long term performance and reactivity of the 3.2% Ni/Fe bimetallic nano-scale particles, weekly spikes of 350
mg
L
−1 TCE were injected into a 3
g
L
−1 nano-scale particle batch reactor. Results showed that the bimetallic nano-scale particles had the ability to reduce 1750
mg
L
−1 TCE and remained active for at least 13
weeks.
Democracy as a Latent Variable Treier, Shawn; Jackman, Simon
American journal of political science,
01/2008, Letnik:
52, Številka:
1
Journal Article
Recenzirano
We apply formal, statistical measurement models to the Polity indicators, used widely in studies of international relations to measure democracy. In so doing, we make explicit the hitherto implicit ...assumptions underlying scales built using the Polity indicators. Modeling democracy as a latent variable allows us to assess the "noise" (measurement error) in the resulting measure. We show that this measurement error is considerable and has substantive consequences when using a measure of democracy as an independent variable in cross-national statistical analyses. Our analysis suggests that skepticism as to the precision of the Polity democracy scale is well founded and that many researchers have been overly sanguine about the properties of the Polity democracy scale in applied statistical work.
Iron (Fe) nanoparticles are increasingly being employed for the remediation of Chlorinated Aliphatic Hydrocarbon (CAH) contaminated sites. However, these particles have recently been reported to be ...cytotoxic to bacterial cells, and may therefore have a negative impact on exposed microbial communities. The overall objective of this study was to investigate the impact of Fe nanoparticles on the biodegradation of CAHs by an indigenous dechlorinating bacterial community. Also, to determine the most appropriate combination and/or application of bimetallic (Ni/Fe) nanoparticles and dechlorinating bacteria for the remediation of CAH contaminated sites. Addition of Fe nanoparticles to groundwater collected from a CAH contaminated site in Derby, UK, led to a decrease in the oxidation–reduction potential (ORP) and an increase in pH. The biological degradation rate of TCE was observed to progressively decrease in the presence of increasing Fe nanoparticle concentrations; which ranged from 0.01 to 0.1
g
L
−1, and cease completely at concentrations of 0.3
g
L
−1 or above. Concentrations greater than 0.3
g
L
−1 led to a decline in viable bacterial counts and the inhibition of biological sulphate reduction. The most appropriate means of combining bimetallic (Ni/Fe) nanoparticles and indigenous dechlorinating bacteria was to employ a two step process: initially stimulating the biodegradation of TCE using acetate, followed by the addition of bimetallic nanoparticles to degrade the remaining cis-1,2-DCE and VC.
Surveys are a key tool for understanding political behavior, but they are subject to biases that render their estimates about the frequency of socially desirable behaviors inaccurate. For decades the ...American National Election Study (ANES) has overestimated voter turnout, though the causes of this persistent bias are poorly understood. The face-to-face component of the 2012 ANES produced a turnout estimate at least 13 points higher than the benchmark voting-eligible population turnout rate. We consider three explanations for this overestimate in the survey: nonresponse bias, over-reporting and the possibility that the ANES constitutes an inadvertent mobilization treatment. Analysis of turnout data supplied by voter file vendors allows the three phenomena to be measured for the first time in a single survey. We find that over-reporting is the largest contributor, responsible for six percentage points of the turnout overestimate, while nonresponse bias and mobilization account for an additional 4 and 3 percentage points, respectively.
Studies of American politics, particularly legislative politics, rely heavily on measures of the partisanship of a district. We develop a measurement model for this concept, estimating partisanship ...in the absence of election-specific, short-term factors, such as national-level swings specific to particular elections, incumbency advantage, and home-state effects in presidential elections. We estimate the measurement model using electoral returns and district-level demographic characteristics spanning five decades (1952–2000), letting us assess how the distribution of district partisanship has changed over time, in response to population movements and redistricting, particularly via the creation of majority-minority districts. We validate the partisanship measure with an analysis of congressional roll-call data. The model is easily extended to incorporate other indicators of district partisanship, such as survey data.
PDF
