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% This file was created with JabRef 2.7b.
% Encoding: ISO8859_1
@STRING{bio = {Biometrika}}
@STRING{rssb = {}}
@ARTICLE{AitS04,
author = {A\"{\i}t-Sidi-Allal, M},
title = {{A new algorithm for estimating the parameters and their asymptotic
covariance in correlation and association models}},
journal = {Computational Statistics \& Data Analysis},
year = {2004},
volume = {45},
pages = {389--421},
number = {3},
abstract = {An algorithm providing maximum likelihood estimates and their asymptotic
covariance matrix for the parameters in correlation models and association
models is proposed. It is based on a Fisher's scoring type algorithm
using the asymptotic covariance matrix of maximum likelihood estimates
whose expression is clarified. The convergence of the proposed algorithm
is generally quickly obtained, even for large contingency tables,
as illustrated through examples.},
doi = {10.1016/S0167-9473(03)00035-5},
issn = {01679473}
}
@book{Agre13,
abstract = {3rd ed. Machine generated contents note: Preface 1. Introduction: Distributions and Inference for Categorical Data 1 1.1 Categorical Response Data, 1 1.2 Distributions for Categorical Data 1.3 Statistical Inference for Categorical Data 1.4 Statistical Inference for Binomial Parameters 1.5 Statistical Inference for Multinomial Parameters 1.6 Bayesian Inference for Binomial and Multinomial Parameters Notes Exercises 2. Describing Contingency Tables 2.1 Probability Structure for Contingency Tables 2.2 Comparing Two Proportions 2.3 Conditional Association in Stratified 2x2 Tables 2.4 Measuring Association in I x J Tables Notes Exercises 3. Inference for Two-Way Contingency Tables 3.1 Confidence Intervals for Association Parameters 3.2 Testing Independence in Two-Way Contingency Tables 3.3 Following-Up Chi-Squared Tests 3.4 Two-Way Tables with Ordered Classifications 3.5 Small-Sample Inference for Contingency Tables 3.6 Bayesian Inference for Two-Way Contingency Tables 3.7 Extensions for Multiway Tables and Nontabulated Responses Notes Exercises 4. Introduction to Generalized Linear Models 4.1 The Generalized Linear Model 4.2 Generalized Linear Models for Binary Data 4.3 Generalized Linear Models for Counts and Rates 4.4 Moments and Likelihood for Generalized Linear Models 4.5 Inference and Model Checking for Generalized Linear Models 4.6 Fitting Generalized Linear Models 4.7 Quasi-Likelihood and Generalized Linear Models Notes Exercises 5. Logistic Regression 5.1 Interpreting Parameters in Logistic Regression 5.2 Inference for Logistic Regression 5.3 Logistic Models with Categorical Predictors 5.4 Multiple Logistic Regression 5.5 Fitting Logistic Regression Models Notes Exercises 6. Building, Checking, and Applying Logistic Regression Models 6.1 Strategies in Model Selection 6.2 Logistic Regression Diagnostics 6.3 Summarizing the Predictive Power of a Model 6.3 Mantel-Haenszel and Related Methods for Multiple 2x2 Tables 6.4 Detecting and Dealing with Infinite Estimates 6.5 Sample Size and Power Considerations Notes Exercises 7. Alternative Modeling of Binary Response Data 7.1 Probit and Complementary Log-Log Models 7.2 Bayesian Inference for Binary Regression 7.3 Conditional Logistic Regression 7.4 Smoothing: Kernels, Penalized Likelihood, Generalized Additive Models 7.5 Issues in Analyzing High-Dimensional Categorical Data Notes Exercises 8. Models for Multinomial Responses 8.1 Nominal Responses: Baseline-Category Logit Models 8.2 Ordinal Responses: Cumulative Logit Models 8.3 Ordinal Responses: Alternative Models 8.4 Testing Conditional Independence in I? J? K Tables 8.5 Discrete-Choice Models 8.6 Bayesian Modeling of Multinomial Responses Notes Exercises 9. Loglinear Models for Contingency Tables 9.1 Loglinear Models for Two-Way Tables 9.2 Loglinear Models for Independence and Interaction in Three-Way Tables 9.3 Inference for Loglinear Models 9.4 Loglinear Models for Higher Dimensions 9.5 The Loglinear?Logistic Model Connection 9.6 Loglinear Model Fitting: Likelihood Equations and Asymptotic Distributions 9.7 Loglinear Model Fitting: Iterative Methods and their Application Notes Exercises 10. Building and Extending Loglinear Models 10.1 Conditional Independence Graphs and Collapsibility 10.2 Model Selection and Comparison 10.3 Residuals for Detecting Cell-Specific Lack of Fit 10.4 Modeling Ordinal Associations 10.5 Generalized Loglinear and Association Models, Correlation Models, and Correspondence Analysis 10.6 Empty Cells and Sparseness in Modeling Contingency Tables 10.7 Bayesian Loglinear Modeling Notes Exercises 11. Models for Matched Pairs 11.1 Comparing Dependent Proportions 11.2 Conditional Logistic Regression for Binary Matched Pairs 11.3 Marginal Models for Square Contingency Tables 11.4 Symmetry, Quasi-symmetry, and Quasi-independence 11.5 Measuring Agreement Between Observers 11.6 Bradley-Terry Model for Paired Preferences 11.7 Marginal Models and Quasi-symmetry Models for Matched Sets Notes Exercises 12. Clustered Categorical Data: Marginal and Transitional Models 12.1 Marginal Modeling: Maximum Likelihood Approach 12.2 Marginal Modeling: Generalized Estimating Equations Approach 12.3 Quasi-likelihood and Its GEE Multivariate Extension: Details 12.4 Transitional Models: Markov Chain and Time Series Models Notes Exercises 13. Clustered Categorical Data: Random Effects Models 13.1 Random Effects Modeling of Clustered Categorical Data 13.2 Binary Responses: The Logistic-Normal Model 13.3 Examples of Random Effects Models for Binary Data 13.4 Random Effects Models for Multinomial Data 13.5 Multilevel Models 13.6 GLMM Fitting, Inference, and Prediction 13.7 Bayesian Multivariate Categorical Modeling Notes Exercises 14. Other Mixture Models for Discrete Data 14.1 Latent Class Models 14.2 Nonparametric Random Effects Models 14.3 Beta-Binomial Models 14.4 Negative Binomial Regression 14.5 Poisson Regression with Random Effects Notes Exercises 15. Non-Model-Based Classification and Clustering 15.2 Classification: Linear Discriminant Analysis 15.3 Classification: Tree-Structured Prediction 15.4 Cluster Analysis for Categorical Data Notes Exercises 16. Large- and Small-Sample Theory for Parametric Models 16.1 Delta Method 16.2 Asymptotic Distributions of Estimators of Model Parameters and Cell Probabilities 16.3 Asymptotic Distributions of Residuals and Goodness-of-Fit Statistics 16.4 Asymptotic Distributions for Logit/Loglinear Models 16.5 Small-Sample Significance Tests for Contingency Tables 16.6 Small-Sample Confidence Intervals for Categorical Data 16.7 Alternative Estimation Theory for Parametric Models Notes Exercises 17. Historical Tour of Categorical Data Analysis 17.1 Pearson-Yule Association Controversy 17.2 R.A. Fisher's Contributions 17.3 Logistic Regression 17.4 Multiway Contingency Tables and Loglinear Models 17.5 Bayesian Methods for Categorical Data 17.6 A Look Forward, and Backward Appendix A. Statistical Software for Categorical Data Analysis Appendix B. Chi-Squared Distribution Values References Author Index Example Index Subject Index. "A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, logistic regression, loglinear models, models for multinomial (nominal and ordinal) responses, and methods for repeated measurement and other forms of clustered, correlated response data. Chapter headings remain essentially with the exception of a new one on Bayesian inference for parametric models. Other major changes include an expansion of clustered data, new research on analysis of data sets with robust variables, extensive discussions of ordinal data, more on interpretation, and additional exercises throughout the book. R and SAS are now showcased as the software of choice. An author web site with solutions, commentaries, software programs, and data sets is available"-- Introduction: Distributions and inference for categorical data -- Describing contingency tables -- Inference for two-way contingency tables -- Introduction to generalized linear models -- Logistic regression -- Building, checking, and applying logistic regression models -- Alternative modeling of binary response data -- Models for multinomial responses -- Loglinear models for contingency tables -- Building and extending loglinear models -- Models for matched pairs -- Clustered categorical data: marginal and transitional models -- Clustered categorical data: random effects models -- Other mixture models for discrete data -- Non-model-based classification and clustering -- Large- and small-sample theory for multinomial models -- Historical tour of categorical data analysis -- Appendix A: Statistical software for categorical data analysis -- Appendix B: Chi-squared distribution values.},
author = {Agresti, Alan.},
edition = {3rd},
isbn = {9780470463635},
pages = {744},
publisher = {Wiley},
title = {{Categorical data analysis}},
url = {https://www.wiley.com/en-gb/Categorical+Data+Analysis,+3rd+Edition-p-9780470463635},
year = {2013}
}
@ARTICLE{Albert84,
author = {Albert, A. and Anderson, J.A.},
title = {On the existence of maximum likelihood estimates in logistic regression
models},
journal = bio,
year = {1984},
volume = {71},
pages = {1--10},
number = {1},
file = {On the existence of ML estimates in logistic regression_1984.pdf:Albert A/On the existence of ML estimates in logistic regression_1984.pdf:PDF},
owner = {yiannis},
timestamp = {2006.07.16}
}
@ARTICLE{Alho00,
author = {Alho, J M},
title = {{Discussion of Lee (2000)}},
journal = {North American Actuarial Journal},
year = {2000},
volume = {4},
pages = {91--93}
}
@ARTICLE{ada02,
author = {{Americans for Democratic Action}},
title = {2001 voting record: {S}hattered promise of liberal progress.},
journal = {ADA today},
year = {2002},
volume = {57},
pages = {1--17},
number = {1},
editor = {ADA Americans for Democratic Action},
organization = {ADA today},
owner = {yiannis},
timestamp = {2012.04.08},
url = {http://www.adaction.org/media/votingrecords/2001.pdf}
}
@ARTICLE{Ande84,
author = {Anderson, J A},
title = {{Regression and Ordered Categorical Variables}},
journal = {J. R. Statist. Soc. B},
year = {1984},
volume = {46},
pages = {1--30},
number = {1}
}
@ARTICLE{Bart07,
author = {Bartley, Mel and Plewis, Ian},
title = {{Increasing social mobility: an effective policy to reduce health
inequalities}},
journal = {Journal of the Royal Statistical Society: Series A (Statistics in
Society)},
year = {2007},
volume = {170},
pages = {469--481},
number = {2},
doi = {10.1111/j.1467-985X.2006.00464.x},
file = {:home/stsdan/Dropbox/References/Bartley, Plewis - 2007 - Increasing social mobility an effective policy to reduce health inequalities.pdf:pdf},
issn = {0964-1998}
}
@TECHREPORT{Batc07,
author = {Batchelor, A and Turner, H L and Firth, D},
title = {{Nonlinear Discrete-Time Hazard Models for Entry into Marriage.}},
institution = {CRiSM},
year = {2007},
number = {Paper 07-16},
address = {$\backslash$url\{http://www.warwick.ac.uk/go/crism/research/working\_papers/2007/paper07-16\}}
}
@ARTICLE{Beck90,
author = {Becker, Mark P.},
title = {{Algorithm AS 253: Maximum Likelihood Estimation of the RC(M) Association
Model}},
journal = {Journal of the Royal Statistical Society. Series C (Applied Statistics)},
year = {1990},
volume = {39},
pages = {152 -- 167},
number = {1},
url = {http://www.jstor.org/stable/2347833}
}
@ARTICLE{Boot96,
author = {Booth, H},
title = {{Demographic forecasting: 1980 to 2005 in review}},
journal = {International Journal of Forecasting},
year = {2006},
volume = {22},
pages = {547--581},
number = {3},
abstract = {Approaches and developments in demographic and population forecasting
since 1980 are reviewed. Three approaches to forecasting demographic
processes are extrapolation, expectation (individual-level birth
expectations or population-level opinions of experts), and theory-based
structural modelling involving exogenous variables. Models include
0–3 factors (age, period and cohort). Decomposition and disaggregation
are also used in multistate models, including macrosimulation and
microsimulation. Forecasting demographic change is difficult; accuracy
depends on the particular situation or trends, but it is not clear
when a method will perform best. Estimates of uncertainty (model-based
ex ante error, expert-opinion-based ex ante error, and ex post error)
differ; uncertainty estimation is highly uncertain. Probabilistic
population forecasts are based on stochastic population renewal or
random scenarios. The approaches to population forecasting, demographic
process forecasting and error estimation are closely linked. Complementary
methods that combine approaches are increasingly employed. The paper
summarises developments, assesses progress and considers the future.},
doi = {10.1016/j.ijforecast.2006.04.001},
issn = {01692070},
keywords = {causal models,demographic modelling,disaggregation,expectations,extrapolation,fertility,migration,mortality,population
forecasting}
}
@ARTICLE{Boyl09,
author = {Boyle, Paul J and Norman, Paul and Popham, Frank},
title = {{Social mobility: evidence that it can widen health inequalities.}},
journal = {Social science \& medicine (1982)},
year = {2009},
volume = {68},
pages = {1835--42},
number = {10},
abstract = {Numerous studies consider the role of social, or occupational, mobility
on health inequalities. A common conclusion is that social mobility
constrains, rather than widens, social class health inequalities.
It is argued that such 'gradient constraint' occurs because movers
into higher social classes tend to have poorer health than those
they join, while movers into lower social classes tend to have better
health than those they join. This has led to the suggestion that
increasing social mobility may be an effective policy to reduce health
inequalities. However, this raises a paradox as many studies also
show that health inequalities are widening. We compare class mobility
and deprivation mobility between 1971 and 1991 with health in 1991
in England and Wales. In both cases, the health in 1991 of the 'mobile'
tended to fall between that of those they left and those they joined.
In comparison to the socially stable, the gradient was thus constrained.
However, comparing the health in 1991 of everyone by their class/deprivation
position in 1991 and 1971, the overall social class health gradient
was little different, while the deprivation health gap was considerably
wider in 1991. These results show that a reduction in inequalities
is not a necessary consequence if the health of 'mobile' people falls
between that of those they left and those they joined and this is
particularly the case for deprivation mobility.},
doi = {10.1016/j.socscimed.2009.02.051},
issn = {0277-9536},
keywords = {England,Health Status Disparities,Humans,Longitudinal Studies,Social
Class,Social Mobility,Wales},
pmid = {19342136},
url = {http://dx.doi.org/10.1016/j.socscimed.2009.02.051}
}
@ARTICLE{BrouDenuVerm02,
author = {Brouhns, N and Denuit, M and Vermunt, J K},
title = {{A Poisson log-bilinear regression approach to the construction of
projected lifetables}},
journal = {Insurance Mathematics and Economics},
year = {2002},
volume = {31},
pages = {373--393},
file = {:home/stsdan/Dropbox/References/Brouhns, Denuit, Vermunt - 2002 - A Poisson log-bilinear regression approach to the construction of projected lifetables.pdf:pdf}
}
@ARTICLE{Bull02,
author = {Bull, S. B. and Mak, C. and Greenwood, C.M.T.},
title = {A modified score function estimator for multinomial logistic regression
in small samples},
journal = {Computational Statistics and Data Analysis},
year = {2002},
volume = {39},
pages = {57--74},
file = {A modified score function estimator for multinomial logistic regression in small samples_2002.pdf:/home/yiannis/Desktop/My Stuff/Work/Warwick/My Papers Library/Bull SV/A modified score function estimator for multinomial logistic regression in small samples_2002.pdf:PDF},
owner = {yiannis},
timestamp = {2006.07.16}
}
@UNPUBLISHED{ButtHabe10,
author = {{Butt, Zoltan; Haberman}, Steve},
title = {{Ilc: A collection of R functions for fitting a class of Lee-Carter
mortality models using iterative fitting algorithms.}},
year = {2009},
annote = {undefined},
institution = {Cass Business School},
pages = {46 pages},
series = {Actuarial Research Paper},
url = {http://www.cass.city.ac.uk/facact/research/reports/190ARP.pdf}
}
@ARTICLE{CairBlakDow09,
author = {Cairns, A.J.G. and Blake, D. and Dowd, K. and Coughlan, G. and Epstein,
D. and Ong, A. and Balevich, I. A.},
title = {{Quantitative comparison of stochastic mortality models using data
from England \& Wales and the United States}},
journal = {North American Actuarial Journal},
year = {2009},
volume = {13},
pages = {1--35},
number = {1},
annote = {undefined},
url = {http://www.soa.org/library/journals/north-american-actuarial-journal/2009/no-01/naaj-2009-vol13-no1-balevich.pdf}
}
@ARTICLE{CatcMorg97,
author = {Catchpole, E A and Morgan, B J T},
title = {{Detecting parameter redundancy}},
journal = {Biometrika},
year = {1997},
volume = {84},
pages = {187--196}
}
@ARTICLE{Caut98,
author = {Cautres, B and Heath, A F and Firth, D},
title = {{Class, religion and vote in Britain and France}},
journal = {La Lettre de la Maison Fran\{\c{c}\}aise},
year = {1998},
volume = {8}
}
@ARTICLE{Chris09,
author = {Christensen, Kaare and Doblhammer, Gabriele and Rau, Roland and Vaupel,
James W},
title = {{Ageing populations: the challenges ahead}},
journal = {The Lancet},
year = {2009},
volume = {374},
pages = {1196--1208},
number = {9696},
doi = {10.1016/S0140-6736(09)61460-4},
issn = {01406736}
}
@ARTICLE{Clau05,
author = {Claussen, Bjorgulf and Smits, Jeroen and Naess, Oyvind and {Davey
Smith}, George},
title = {{Intragenerational mobility and mortality in Oslo: social selection
versus social causation.}},
journal = {Social science \& medicine (1982)},
year = {2005},
volume = {61},
pages = {2513--20},
number = {12},
abstract = {We investigate the relative importance of the selection and causation
hypotheses of social inequalities in mortality, and estimate upper
and lower bounds for the gender-specific mobility effects. For all
inhabitants of Oslo aged 50-69 years in 1990, we knew their social
class in 1960 and 1980 and whether they died between 1990 and 1994.
Analysing these data with diagonal reference models, we found those
moving upwards in the social hierarchy to have lower mortality rates
than their class of origin but higher mortality rates than their
class of destination. A corresponding pattern was found for those
moving downwards. Thus, social mobility may increase or constrict
the social class mortality divide. We estimated the upper bound to
the mobility effect to be an increase of 52\% for males and 28\%
for females (situation of no causation) and the lower bound to be
a decrease of 24\% for males and 21\% for females (situation of no
selection). Because both selection and causation effects are expected
to play a role and to work in opposite directions, the resulting
effect of social mobility on the mortality divide may be rather small.},
doi = {10.1016/j.socscimed.2005.04.045},
issn = {0277-9536},
keywords = {Adult,Aged,Causality,Female,Health Surveys,Hierarchy,Humans,Male,Middle
Aged,Mortality,Norway,Norway: epidemiology,Occupations,Occupations:
classification,Occupations: statistics \& numerical data,Sex Factors,Social,Social
Mobility,Social Mobility: statistics \& numerical data,Socioeconomic
Factors},
pmid = {15992981}
}
@ARTICLE{Clif93,
author = {Clifford, P and Heath, A F},
title = {{The political consequences of social mobility}},
journal = {J. Roy. Stat. Soc. A},
year = {1993},
volume = {156},
pages = {51--61},
number = {1},
file = {:home/stsdan/Dropbox/References//Clifford, Heath - 1993 - The political consequences of social mobility.pdf:pdf}
}
@ARTICLE{vanE,
author = {van Eeuwijk, F A},
title = {{Multiplicative interaction in generalized linear models}},
journal = {Biometrics},
year = {1995},
volume = {51},
pages = {1017--1032}
}
@BOOK{Erik92,
title = {{The constant flux}},
publisher = {Oxford: Clarendon Press},
year = {1992},
author = {Erikson, R and Goldthorpe, J H}
}
@ARTICLE{Erik82,
author = {Erikson, R and Goldthorpe, J H and Portocarero, L},
title = {{Social fluidity in industrial nations: England, France and Sweden}},
journal = {British Journal of Sociology},
year = {1982},
volume = {33},
pages = {1--34},
file = {:home/stsdan/Dropbox/References//Erikson, Goldthorpe, Portocarero - 1982 - Social fluidity in industrial nations England, France and Sweden.pdf:pdf}
}
@INPROCEEDINGS{Firt98,
author = {Firth, David},
title = {{LLAMA: An object-oriented system for log multiplicative models}},
booktitle = {COMPSTAT 1998, Proceedings in Computational Statistics},
year = {1998},
editor = {Payne, Roger and Green, Peter},
pages = {305--310},
publisher = {Heidelberg: Physica-Verlag}
}
@ARTICLE{Firt03,
author = {Firth, D},
title = {{Overcoming the reference category problem in the presentation of
statistical models}},
journal = {Sociological Methodology},
year = {2003},
volume = {33},
pages = {1--18}
}
@ARTICLE{Firth93,
author = {David Firth},
title = {Bias Reduction of maximum likelihood estimates},
journal = bio,
year = {1993},
volume = {80},
pages = {27--38},
number = {1},
file = {Bias Reduction of ML Estimates_1993.pdf:Firth D/Bias Reduction of ML Estimates_1993.pdf:PDF},
owner = {yiannis},
timestamp = {2006.07.17}
}
@ARTICLE{firt:04,
author = {Firth, D and de Menezes, R X},
title = {{Quasi-variances}},
journal = {Biometrika},
year = {2004},
volume = {91},
pages = {65--80}
}
@UNPUBLISHED{GNMpaper,
author = {David Firth and Heather L Turner and Ioannis Kosmidis},
title = {Generalized Nonlinear Models in Practice},
note = {Work in progress.},
year = {2012},
owner = {heather},
timestamp = {2012.07.12}
}
@ARTICLE{Gabr98,
author = {Gabriel, K R},
title = {{Generalised bilinear regression}},
journal = {Biometrika},
year = {1998},
volume = {85},
pages = {689--700},
file = {:home/stsdan/Dropbox/References/Gabriel - 1998 - Generalised bilinear regression.pdf:pdf}
}
@INBOOK{Ganz04,
chapter = {14},
pages = {345--381},
title = {{Recent trends in intergenerational occupational class reproduction
in the Netherlands 1970-99}},
publisher = {Oxford University Press},
year = {2004},
editor = {Breen, Richard},
author = {Ganzeboom, Harry B. G. and Luijkx, Ruud},
booktitle = {Social Mobility in Europe},
isbn = {978-0-19-925845-1}
}
@ARTICLE{Good85,
author = {Goodman, L A},
title = {{The analysis of cross-classified data having ordered and/or unordered
categories: Association models, correlation models, and asymmetry
models for contingency tables with or without missing entries.}},
journal = {Ann Statist},
year = {1985},
volume = {13},
pages = {10--69}
}
@ARTICLE{Good79a,
author = {Goodman, L A},
title = {{Simple models for the analysis of association in cross-classifications
having ordered categories}},
journal = {J. Amer. Statist. Assoc.},
year = {1979},
volume = {74},
pages = {537--552},
file = {:home/stsdan/Dropbox/References//Goodman - 1979 - Simple models for the analysis of association in cross-classifications having ordered categories.pdf:pdf}
}
@ARTICLE{Good79b,
author = {Goodman, Leo A.},
title = {{Multiplicative models for the analysis of occupational mobility
tables and other kinds of cross-classification tables}},
journal = {The American Journal of Sociology},
year = {1979},
volume = {84},
pages = {804--819},
number = {4},
url = {http://0-www.jstor.org.pugwash.lib.warwick.ac.uk/stable/2778025}
}
@ARTICLE{HabeRens09,
author = {Haberman, Steven and Renshaw, Arthur},
title = {{On age-period-cohort parametric mortality rate projections}},
journal = {Insurance: Mathematics and Economics},
year = {2009},
volume = {45},
pages = {255--270},
number = {2},
abstract = {An enhanced version of the Lee–Carter modelling approach to mortality
forecasting, which has been extended to include an age modulated
cohort index in addition to the standard age modulated period index,
is described and tested for prediction robustness. Life expectancy
and annuity value predictions, at pensioner ages and for various
periods are compared, both with and without the age modulated cohort
index, for the England \& Wales male mortality experience. The simulation
of prediction intervals for these indices of interest is discussed
in detail.},
doi = {10.1016/j.insmatheco.2009.07.006},
issn = {01676687},
keywords = {age-period-cohort effects,back-fitting,data truncation,forecast statistics,mortality
forecasting}
}
@ARTICLE{Habe95,
author = {Haberman, Shelby J.},
title = {{Computation of maximum likelihood estimates in association models}},
journal = {Journal of the American Statistical Association},
year = {1995},
volume = {90},
pages = {1438 -- 1446},
number = {432},
url = {http://www.jstor.org/stable/2291536}
}
@ARTICLE{Hart09,
author = {Hart, Carole L and {Davey Smith}, George and Upton, Mark N and Watt,
Graham C M},
title = {{Alcohol consumption behaviours and social mobility in men and women
of the Midspan Family study.}},
journal = {Alcohol and alcoholism},
year = {2009},
volume = {44},
pages = {332--6},
number = {3},
abstract = {AIMS: The aim of this study was to investigate relationships between
alcohol consumption and social mobility in a cohort study in Scotland.
METHODS: 1040 sons and 1298 daughters aged 30-59 from 1477 families
reported their alcohol consumption from which was derived: weekly
units (1 UK unit being 8 g ethanol), exceeding daily or weekly limits,
binge drinking and consuming alcohol on 5+ days per week. Own and
father's social class were available enabling social mobility to
be investigated. RESULTS: More downwardly mobile men exceeded the
weekly limit, the daily limit, were defined as binge drinkers and
drank the most units per week of the four social mobility groups.
Stable non-manual women were more likely to consume alcohol on 5+
days a week but very few were binge drinkers. Stable non-manual and
upwardly mobile men and women were more likely to drink wine, and
downwardly mobile men to drink beer. CONCLUSIONS: Downward mobility
was associated with less favourable alcohol behaviours, especially
in men. Wine consumption was more closely related to the social mobility
groups than beer and spirits consumption. Drinking patterns could
both influence and be influenced by social mobility.},
doi = {10.1093/alcalc/agn125},
file = {:home/stsdan/Dropbox/References/Hart et al. - 2009 - Alcohol consumption behaviours and social mobility in men and women of the Midspan Family study.pdf:pdf},
issn = {1464-3502},
keywords = {Adult,Alcohol Drinking,Alcohol Drinking: economics,Alcohol Drinking:
epidemiology,Cohort Studies,Family,Female,Humans,Male,Middle Aged,Prospective
Studies,Social Class,Social Mobility,Socioeconomic Factors},
pmid = {19168459}
}
@ARTICLE{Haus84a,
author = {Hauser, Robert M.},
title = {{Vertical class mobility in England, France, and Sweden}},
journal = {Acta Sociologica},
year = {1984},
volume = {27},
pages = {87},
number = {2},
doi = {10.1177/000169938402700201},
isbn = {10.1177/000169938402700201},
issn = {1502-3869},
publisher = {SAGE Publications}
}
@ARTICLE{Haus84b,
author = {Hauser, Robert M.},
title = {{Corrigenda: Vertical class mobility in England, France, and Sweden}},
journal = {Acta Sociologica},
year = {1984},
volume = {27},
pages = {387--90},
number = {4}
}
@ARTICLE{Heinze02,
author = {Georg Heinze and Michael Schemper},
title = {A solution to the problem of separation in logistic regression},
journal = {Statistics in Medicine},
year = {2002},
volume = {21},
pages = {2409--2419},
file = {A solution to the problem of separation in logistic regression_2002.pdf:Heinze G/A solution to the problem of separation in logistic regression_2002.pdf:PDF},
owner = {yiannis},
timestamp = {2006.07.17}
}
@ARTICLE{Kosmidis12,
author = {Kosmidis, I.},
title = {Improved estimation in cumulative link models},
journal = {ArXiv e-prints},
year = {2012},
volume = {1204.0105},
adsnote = {Provided by the SAO/NASA Astrophysics Data System},
adsurl = {http://adsabs.harvard.edu/abs/2012arXiv1204.0105K},
archiveprefix = {arXiv},
eprint = {1204.0105},
keywords = {Statistics - Methodology, Statistics - Computation, 62F03, 62F10,
62F12, 62J12},
owner = {yiannis},
primaryclass = {stat.ME},
timestamp = {2012.04.07},
url = {http://arxiv.org/abs/1204.0105}
}
@TECHREPORT{Kosmidis09a,
author = {Kosmidis, I},
title = {On iterative adjustment of responses for the reduction of bias in
binary regression models},
institution = {CRiSM working paper series},
year = {2009},
number = {09-36},
owner = {yiannis},
timestamp = {2010.05.16}
}
@ARTICLE{Kosmidis11,
author = {Kosmidis, I and Firth, D},
title = {Multinomial logit bias reduction via the Poisson log-linear model},
journal = {Biometrika},
year = {2011},
volume = {98},
pages = {755-759},
number = {3},
owner = {yiannis},
timestamp = {2010.05.16}
}
@ARTICLE{Kosmidis09,
author = {Kosmidis, Ioannis and Firth, David},
title = {Bias reduction in exponential family nonlinear models},
journal = {Biometrika},
year = {2009},
volume = {96},
pages = {793--804},
number = {4},
abstract = {In Firth (1993, Biometrika) it was shown how the leading term in the
asymptotic bias of the maximum likelihood estimator is removed by
adjusting the score vector, and that in canonical-link generalized
linear models the method is equivalent to maximizing a penalized
likelihood that is easily implemented via iterative adjustment of
the data. Here a more general family of bias-reducing adjustments
is developed for a broad class of univariate and multivariate generalized
nonlinear models. The resulting formulae for the adjusted score vector
are computationally convenient, and in univariate models they directly
suggest implementation through an iterative scheme of data adjustment.
For generalized linear models a necessary and sufficient condition
is given for the existence of a penalized likelihood interpretation
of the method. An illustrative application to the Goodman row-column
association model shows how the computational simplicity and statistical
benefits of bias reduction extend beyond generalized linear models.},
doi = {10.1093/biomet/asp055},
eprint = {http://biomet.oxfordjournals.org/cgi/reprint/96/4/793.pdf},
owner = {yiannis},
timestamp = {2012.04.09}
}
@ARTICLE{LeeCart92,
author = {Lee, R D and Carter, L},
title = {{Modelling and forecasting the time series of \{US\} mortality}},
journal = {Journal of the American Statistical Association},
year = {1992},
volume = {87},
pages = {659--671},
file = {:home/stsdan/Dropbox/References/Lee, Carter - 1992 - Modelling and forecasting the time series of \{US\} mortality.pdf:pdf}
}
@ARTICLE{deLe06,
author = {de Leeuw, J},
title = {{Principal component analysis of binary data by iterated singular
value decomposition}},
journal = {Comp. Stat. Data Anal.},
year = {2006},
volume = {50},
pages = {21--39},
number = {1}
}
@ARTICLE{Louc10,
author = {Loucks, Eric B and Pilote, Louise and Lynch, John W and Richard,
Hugues and Almeida, Nisha D and Benjamin, Emelia J and Murabito,
Joanne M},
title = {{Life course socioeconomic position is associated with inflammatory
markers: the Framingham Offspring Study.}},
journal = {Social science medicine},
year = {2010},
volume = {71},
pages = {187--195},
number = {1},
abstract = {Associations between life course socioeconomic position (SEP) and
novel biological risk markers for coronary heart disease such as
inflammatory markers are not well understood. Most studies demonstrate
inverse associations of life course SEP with C-reactive protein (CRP),
interleukin-6 (IL-6) and fibrinogen, however little is known about
associations between life course SEP and other inflammatory markers
including intercellular adhesion molecule-1 (ICAM-1), tumor necrosis
factor II (TNFR2), lipoprotein phospholipase A2 (Lp-PLA2) activity,
monocyte chemoattractant protein-1 (MCP-1) or P-selectin. The objectives
of this analysis were to determine whether three life course SEP
frameworks ("accumulation of risk", "social mobility" and "sensitive
periods") are associated with the aforementioned inflammatory markers.
We examined 1413 Framingham Offspring Study participants (mean age
61.2+/-8.6 years, 54\% women), using multivariable regression analyses.
In age- and sex-adjusted regression analyses, cumulative SEP ("accumulation
of risk" SEP framework), for low vs. high SEP, was inversely associated
with CRP, IL-6, ICAM-1, TNFR2, Lp-PLA2 activity, MCP-1 and fibrinogen.
We found that there were few consistent trends between social mobility
trajectories and most inflammatory markers. Own educational attainment
was inversely associated with 7 of 8 studied inflammatory markers,
while father's education, father's occupation and own occupation
were inversely associated with 4, 5 and 4 inflammatory markers, respectively,
in age- and sex-adjusted analyses. The strengths of association between
SEP and inflammatory markers were typically substantially accounted
for by CHD risk markers (smoking, body mass index, systolic blood
pressure, total:HDL cholesterol ratio, fasting glucose, medications,
depressive symptomatology) suggesting these may be important mechanisms
that explain associations between SEP and the studied inflammatory
markers.},
institution = {Department of Community Health, Epidemiology Section, Brown University,
Rhode Island, United States. eric.loucks@brown.edu},
publisher = {Elsevier Ltd},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2895737\&tool=pmcentrez\&rendertype=abstract}
}
@BOOK{McCu89,
title = {{Generalized Linear Models (\{S\}econd Edition)}},
publisher = {Chapman \& Hall Ltd},
year = {1989},
author = {McCullagh, P and Nelder, J A},
pages = {500}
}
@ARTICLE{Mehrabi95,
author = {Mehrabi, Yadollah and Matthews, J. N. S.},
title = {Likelihood-based Methods for Bias Reduction in Limiting Dilution
Assays},
journal = {Biometrics},
year = {1995},
volume = {51},
pages = {1543--1549},
file = {Likelihood-Based Methods for Bias Reduction in Limiting Dilution Assays_1995.pdf:Mehrabi Y/Likelihood-Based Methods for Bias Reduction in Limiting Dilution Assays_1995.pdf:PDF},
keywords = {Jackknife},
owner = {yiannis},
timestamp = {2012.04.07}
}
@ARTICLE{Mond03,
author = {Monden, Christiaan W. S. and van Lenthe, Frank and de Graaf, Nan
Dirk and Kraaykamp, Gerbert},
title = {{Partner's and own education: does who you live with matter for self-assessed
health, smoking and excessive alcohol consumption?}},
journal = {Social Science \& Medicine},
year = {2003},
volume = {57},
pages = {11},
number = {10},
abstract = {This study analyses the importance of partner status and partner's
education, adjusted for own education, on self-assessed health, smoking
and excessive alcohol consumption. The relationship between socio-economic
factors and health-related outcomes is traditionally studied from
an individual perspective. Recently, applying social–ecological
models that include socio-economic factors on various social levels
is becoming popular. We argue that partners are an important influence
on individual health and health-related behaviour at the household
level. Therefore, we include partners in the analysis of educational
health inequalities. Using data of almost 40,000 individuals (with
almost 15,000 Dutch cohabiting couples), aged 25–74 years, who
participated in the Netherlands Health Interview Survey between 1989
and 1996, we test hypotheses on the importance of own and partner's
education. We apply advanced logistic regression models that are
especially suitable for studying the relative influence of partners’
education. Controlled for own education, partner's education is significantly
associated with self-assessed health and smoking, for men and women.
Accounting for both partners’ education the social gradient in
self-assessed health and smoking is steeper than based on own or
partner's education alone. The social gradient in health is underestimated
by not considering partner's education, especially for women.},
doi = {10.1016/S0277-9536(03)00055-8}
}
@ARTICLE{Pate08,
author = {Paterson, Lindsay},
title = {{Political attitudes, social participation and social mobility: a
longitudinal analysis.}},
journal = {British Journal of Sociology},
year = {2008},
volume = {59},
pages = {413--434},
number = {3},
abstract = {It is often suggested that the political attitudes and social participation
which have underpinned the welfare-state democracies have depended
on large amounts of upward social mobility. The demographic heterogeneity
of the service class, according to this view, induced in them a willingness
to lead a common political project seeking to establish a common
social citizenship. As the amount of upward mobility stagnates or
even begins to fall, it has then further been claimed that there
might emerge a degree of ideological closure in the service class
that might erode their commitment to civic values. The 1958 British
birth cohort study is used to investigate this question. Longitudinal
data are invaluable here because they allow us to distinguish between
two hypotheses: that upward mobility as such has induced in the service
class certain attitudes and propensities to participate, or that
the more important influence is the early socialization through which
upwardly mobile people went. The conclusion of the analysis is that,
although the civic values of the service class have not depended
on upward mobility, this is much more true of cognitively able people
than of others, and so is dependent on the somewhat meritocratic
basis of selection into the salariat.},
institution = {School of Education, University of Edinburgh. lindsay.paterson@ed.ac.uk},
pmid = {18782148},
url = {http://www.ncbi.nlm.nih.gov/pubmed/18782148}
}
@ARTICLE{Pear09,
author = {Pearce, M S and Thomson, W M and Walls, A W G and Steele, J G},
title = {{Lifecourse socio-economic mobility and oral health in middle age.}},
journal = {Journal of Dental Research},
year = {2009},
volume = {88},
pages = {938--941},
number = {10},
abstract = {Socio-economic variations in health exist for a wide range of health
outcomes, including oral health and oral-health-related quality of
life (OHRQoL). Less is known regarding how socio-economic trajectories
may influence oral health and OHRQoL. This study examined whether
social mobility is related to the number of teeth retained by age
50 years and OHRQoL measured at the same time, using data from the
Newcastle Thousand Families Study, a birth cohort established in
1947. Women remaining in the non-manual class had the greatest tooth
retention. While promotion of a healthier lifestyle and continued
improvements in oral hygiene throughout life appear to be the public
health interventions most likely to improve oral health into middle
age, there may be sub-groups of the population on which different
approaches in terms of public health interventions need to be focused.},
institution = {Institute of Health and Society, Newcastle University, Sir James
Spence Institute, Royal Victoria Infirmary, Newcastle upon Tyne,
NE1 4LP, UK. M.S.Pearce@ncl.ac.uk},
pmid = {19783803}
}
@ARTICLE{RensHabe06,
author = {Renshaw, A and Haberman, S},
title = {{A cohort-based extension to the Lee-Carter model for mortality reduction
factors}},
journal = {Insurance: Mathematics and Economics},
year = {2006},
volume = {38},
pages = {556--570},
number = {3},
abstract = {The Lee–Carter modelling framework is extended through the introduction
of a wider class of generalised, parametric, non-linear models. This
permits the modelling and extrapolation of age-specific cohort effects
as well as the more familiar age-specific period effects. The choice
of error distribution is generalised.},
doi = {10.1016/j.insmatheco.2005.12.001},
issn = {01676687},
keywords = {cohort effects,generalised non-linear models,mortality projections,mortality
reduction factors,time series}
}
@ARTICLE{RensHabe03,
author = {Renshaw, A and Haberman, S},
title = {{Lee-Carter mortality forecasting: a parallel generalized linear
modelling approach for England and Wales mortality projections}},
journal = {Applied Statistics},
year = {2003},
volume = {52},
pages = {119--137}
}
@ARTICLE{Schm10,
author = {Schmeisser, N and Conway, D I and McKinney, P A and McMahon, A D
and Pohlabeln, H and Marron, M and Benhamou, S and Bouchardy, C and
Macfarlane, G J and Macfarlane, T V and Lagiou, P and Lagiou, A and
Bencko, V and Holc\'{a}tov\'{a}, I and Merletti, F and Richiardi,
L and Kjaerheim, K and Agudo, A and Talamini, R and Polesel, J and
Canova, C and Simonato, L and Lowry, R and Znaor, A and Healy, C
and McCarten, B E and Hashibe, M and Brennan, P and Ahrens, W},
title = {{Life course social mobility and risk of upper aerodigestive tract
cancer in men.}},
journal = {European journal of epidemiology},
year = {2010},
volume = {25},
pages = {173--82},
number = {3},
abstract = {The aim of this study was to explore associations between social mobility
and tumours of the upper aero-digestive tract (UADT), focussing on
life-course transitions in social prestige (SP) based on occupational
history. 1,796 cases diagnosed between 1993 and 2005 in ten European
countries were compared with 1585 controls. SP was classified by
the Standard International Occupational Prestige Scale (SIOPS) based
on job histories. SIOPS was categorised in high (H), medium (M) and
low (L). Time weighted average achieved and transitions between SP
with nine trajectories: H --> H, H --> M, H --> L, M --> H, M -->
M, M --> L, L --> H, L --> M and L --> L were analysed. Odds ratios
(ORs) and 95\%-confidence intervals [95\%-CIs] were estimated with
logistic regression models including age, consumption of fruits/vegetables,
study centre, smoking and alcohol consumption. The adjusted OR for
the lowest versus the highest of three categories (time weighted
average of SP) was 1.28 [1.04-1.56]. The distance of SP widened between
cases and controls during working life. The downward trajectory H
--> L gave an OR of 1.71 [0.75-3.87] as compared to H --> H. Subjects
with M --> M and L --> L trajectories ORs were also elevated relative
to subjects with H --> H trajectories. The association between SP
and UADT is not fully explained by confounding factors. Downward
social trajectory during the life course may be an independent risk
factor for UADT cancers.},
doi = {10.1007/s10654-010-9429-5},
issn = {1573-7284},
keywords = {80 and over,Adult,Aged,Europe,Europe: epidemiology,Head and Neck Neoplasms,Head
and Neck Neoplasms: epidemiology,Head and Neck Neoplasms: etiology,Humans,Interviews
as Topic,Male,Middle Aged,Questionnaires,Risk Assessment,Social Class,Social
Mobility,Young Adult},
pmid = {20143252}
}
@BOOK{Sebe89,
title = {{Nonlinear Regression}},
publisher = {Wiley},
year = {1989},
author = {Seber, G A F and Wild, C J}
}
@ARTICLE{Vand02,
author = {van der Slik, F W P and de Graaf, N D and Gerris, J R M},
title = {{Conformity to Parental Rules: Asymmetric Influences of Father's
and Mother's Levels of Education}},
journal = {Europ. Soc. Rev.},
year = {2002},
volume = {18},
pages = {489--502},
file = {:home/stsdan/Dropbox/References//van der Slik, de Graaf, Gerris - 2002 - Conformity to Parental Rules Asymmetric Influences of Father's and Mother's Levels of Education.pdf:pdf}
}
@ARTICLE{Sobe85,
author = {Sobel, M E},
title = {{Social mobility and fertility revisited: Some new models for the
analysis of the mobility effects hypothesis}},
journal = {Amer. Soc. Rev.},
year = {1985},
volume = {50},
pages = {699--712},
file = {:home/stsdan/Dropbox/References//Sobel - 1985 - Social mobility and fertility revisited Some new models for the analysis of the mobility effects hypothesis.pdf:pdf}
}
@ARTICLE{Sobe81,
author = {Sobel, M E},
title = {{Diagonal mobility models: A substantively motivated class of designs
for the analysis of mobility effects}},
journal = {Amer. Soc. Rev.},
year = {1981},
volume = {46},
pages = {893--906},
file = {:home/stsdan/Dropbox/References//Sobel - 1981 - Diagonal mobility models A substantively motivated class of designs for the analysis of mobility effects.pdf:pdf}
}
@INBOOK{Tabeau2002,
pages = {1--32},
title = {{A Review of Demographic Forecasting Models for Mortality}},
publisher = {Kluwer Academic Publishers},
year = {2002},
editor = {Tabeau, Ewa and {Berg Jeths}, Anneke and Heathcote, Christopher},
author = {Tabeau, Ewa},
volume = {9},
series = {European Studies of Population},
address = {Dordrecht},
abstract = {The goal of Chapter 1 is to describe and comment on the methods and
approaches that have been in use or have emerged in recent years.
Section 1.1 introduces the most common classifications of forecasting
models for mortality. Section 1.2 is devoted to a brief historical
review of parameterisation functions. In this context, attention
is paid to prediction based on parameterised age schedules, in particular
by using time series models. Section 1.3 focuses on the (statistical
association) models of Lee and Carter and Section 1.4 characterises
the (log-linear) age-period-cohort models. In Section 1.5 the reader
can find a review of the methods used in international statistical
practice and in Section 1.6 the importance of uncertainty in forecasting
is addressed. Section 1.7 outlines the prospects for modelling and
forecasting mortality as seen from the perspective of this chapter.},
booktitle = {Forecasting Mortality in Developed Countries},
doi = {10.1007/0-306-47562-6},
isbn = {0-7923-6833-9}
}
@ARTICLE{Tiikkaja2009,
author = {Tiikkaja, Sanna and Hemstr\"{o}m, Orjan and V\aa ger\"{o}, Denny},
title = {{Intergenerational class mobility and cardiovascular mortality among
Swedish women: a population-based register study.}},
journal = {Social science \& medicine (1982)},
year = {2009},
volume = {68},
pages = {733--9},
number = {4},
abstract = {Class inequalities in cardiovascular disease (CVD) mortality are well
documented, but the impact of intergenerational class mobility on
CVD mortality among women has not been studied thoroughly. We examined
whether women's mobility trajectories might contribute to CVD mortality
beyond what could be expected from their childhood and adult social
class position. The Swedish Work and Mortality Data Base provided
childhood (1960) and adulthood (1990) social indicators. Women born
1945-59 (N=791 846) were followed up for CVD mortality 1990-2002
(2019 deaths) by means of logistic regression analysis. CVD mortality
risks were estimated for 16 mobility trajectories. Gross and net
impact of four childhood and four adult classes, based on occupation,
were analysed for mortality in ischemic heart disease (IHD), stroke,
other CVD, - and all CVD. Differences between the two most extreme
trajectories were 10-fold, but the common trajectory of moving from
manual to non-manual position was linked to only a slight excess
mortality (OR=1.26) compared to the equally common trajectory of
maintaining a stable non-manual position (reference category). Moving
into adult manual class resulted in an elevated CVD mortality whatever
the childhood position (ORs varied between 1.42 and 2.24). After
adjustment for adult class, childhood class had some effect, in particular
there was a low risk of coming from a self-employed childhood class
on all outcomes (all ORs around=0.80). A woman's own education had
a stronger influence on the mortality estimates than did household
income. Social mobility trajectories among Swedish women are linked
to their CVD mortality risk. Educational achievement seems to be
a key factor for intergenerational continuity and discontinuity in
class-related risk of CVD mortality among Swedish women. However,
on mutual adjustment, adult class was much more closely related to
CVD mortality than was class in childhood.},
doi = {10.1016/j.socscimed.2008.11.017},
issn = {0277-9536},
keywords = {Aged,Cardiovascular Diseases,Cardiovascular Diseases: mortality,Cohort
Studies,Female,Humans,Middle Aged,Risk Factors,Social Class,Social