Share
Statistical Analysis of Continuous Data
Four Volume Set
Edited by:
- Roger Penn - Queen's University Belfast, UK
- Damon Berridge - University of Lancaster, UK
Other Titles in:
Data Collection & Analysis
Data Collection & Analysis
June 2013 | 1 800 pages | SAGE Publications Ltd
This new four-volume collection tracks the development of statistical methods for continuous, or interval-scale data. Examples of such data occurring in the social sciences include indicators of educational attainment (for example, GCSE scores) and psychometric measures of intelligence. Framed by a new contextualising introduction, the volumes are organised thematically, covering key areas to enable a well-rounded and comprehensive understanding of the discipline:
Volume One: Statistical Foundations for the Analysis of Continuous Data
Volume Two: Basic Principles for the Statistical Modelling of Continuous Data
Volume Three: Multivariate Analyses of Continuous Data
Volume Four: Statistical Modelling of Multivariate Continuous Data
VOLUME ONE: STATISTICAL FOUNDATIONS FOR THE ANALYSIS OF CONTINUOUS DATA
F. Edgeworth
Methods of Statistics
F. Edgeworth
Some New Methods of Measuring Variation in General Prices
Karl Pearson
Contributions to the Mathematical Theory of Evolution
G. Udny Yule
Notes on the History of Pauperism in England and Wales from 1850, Treated by the Method of Frequency-Curves, with an Introduction on the Method
G. Udny Yule
On the Theory of Correlation
Karl Pearson
Mathematical Contributions to the Theory of Evolution
L. Gossett ('Student')
Probable Error of a Mean
E. Slutsky
On the Criterion of Goodnes -of-Fit of the Regression Lines and on the Best Methods of Fitting Them to the Data
Karl Pearson
Notes on the History of Correlation
R.A. Fisher
On the 'Probable Error' of a Co-Efficient of Correlation Deduced from a Small Sample
R.A. Fisher
The Goodness-of-Fit of Regression Formulae and the Distribution of Regression Co-Efficients
A. Fisher
Applications of 'Students' Distribution
VOLUME TWO: BASIC PRINCIPLES FOR THE STATISTICAL MODELING OF CONTINUOUS DATA
R. Geary
Testing for Normality
G. Box
A General Distribution Theory for a Class of Likelihood Criteria
Henry Scheffe
A Method for Judging All Contrasts in the Analysis of Variance
G. Box and D. Cox
An Analysis of Transformations
Robert Gordon
Issues in Multiple Regression
J. Nelder and R. Wedderburn
Generalized Linear Models
R. Wedderburn
Quasi-Likelihood Functions, Generalized Linear Models and the Gauss-Newton Method
Robert Bendall and A. Afifi
Comparison of Stopping Rules in forward 'Stepwise' Regression
J. Darroch and T. Speed
Additive and Multiplicative Models and Interactions
Bent Jorgensen
Maximum Likelihood Estimation and Large-Sample Inference for Generalized Linear and Non-Linear Regression Models
P. Green
Iteratively Reweighted Least Squares for Maximum Likelihood Estimation and Some Robust and Resistant Alternatives
Alan Miller
Selection of Subsets of Regression Variables
D. Edwards and T. Havranek
A Fast Model Selection Procedure for Large Families of Models
S. Palmer et al
Control of Leaf Expansion in Sunflower (Helianthus anuus L.) by Nitrogen Nutrition
T Crawford et al
Saccadic Eye Movements in Families Multiply Affected with Schizophrenia
VOLUME THREE: MULTIVARIATE ANALYSES OF CONTINUOUS DATA
Harold Hotelling
The Generalization of Student's Ratio
P. Mahalanobis
On the Generalized Distance in Statistics
John Mauchly
Significance Test for Sphericity of a Normal n-Variate Distribution
Radhakrishna Rao
Tests with Discriminant Functions in Multivariate Analysis
S. Wilks
Sample Criteria for Testing Equality of Means, Equality of Variances and Equality of Co-Variances in a Normal Multivariate Distribution
Seymour Geisser and Samuel Greenhouse
An Extension of Box's Results on the Use of the F Distribution in Multivariate Analysis
H. Smith et al
Multivariate Analysis of Variance (MANOVA)
A. Constantine
Some Non-Central Distribution Problems in Multivariate Analysis
T. Anderson
Asymptotic Theory for a Principal Component Analysis
Richard Potthoff and S. Roy
A Generalized Multivariate Analysis of Variance Model Useful Especially for Growth Curve Problems
J. Gower
Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis
E. Williams
The Analysis of Association among Many Variates
N. Day and D. Kerridge
A General Maximum Likelihood Discriminant
H. Friedman and J. Rubin
On Some Invariant Criteria for Grouping Data
C. Khatri and K. Pillai
On the Non-Central Distributions of Two Test Criteria in a Multivariate Analysis of Variance
N. Day
Estimating the Components of a Mixture of Normal Distributions
Huyhn Huynh and Leonard Feldt
Conditions under Which Mean -Square Ratios in Repeated Measurements Designs Have Exact F-Distributions
J. Kettenring
Canonical Analysis of Several Sets of Variables
VOLUME FOUR: STATISTICAL MODELING OF MULTIVARIATE CONTINUOUS DATA
Kenneth Land
Principles of Path Analysis
Otis Dudley Duncan
Contingencies in Constructing Causal Models
Otis Dudley Duncan
Unmeasured Variables in Linear Models for Panel Analysis
Chester Olson
Comparative Robustness of Six Tests in Multivariate Analysis of Variance
P. Bentler
Multivariate Analysis with Latent Variables
P. Bentler and Douglas Bonett
Significance Tests and Goodness-of- Fit in the Analysis of Covariance Structures
Karl Joreskog et al
Analysis of Covariance Structures [with Discussion and Reply]
Karl Joreskog and Dag Sörbom
Recent Developments in Structural Equation Modeling
Nan Laird and James Ware
Random-Effects Models for Longitudinal Data
Paul Holland
Statistics and Causal Inference
James Anderson
Structural Equation Models in the Social and Behavioural Sciences
R. Davies et al
Linear Modeling with Clustered Observations
James Anderson and David Gerbing
Structural Equation Modeling in Practice
Mary Lindstrom and Douglas Bates
Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
Stanley Mulaik et al
Evaluation of Goodness-of-Fit Indices for Structural Equation Models
Barbara Byrne et al
Testing for the Equivalence of Factor Covariance and Mean Structures
Nanny Wermuth and Steffen Lilholt Lauritzen
On Substantive Research Hypotheses, Conditional Independence Graphs and Graphical Chain Models
Robert MacCallum and James Austin
Applications of Structural Equation Modeling in Psychological Research
Bengt Muthen
Beyond Structural Equation Modeling:
Ke-Hai Yuan and Peter Bentler
Multilevel Covariance Structure Analysis by Fitting Multiple Single-Level Models
Roger Penn and Damon Berridge
Modeling Trajectories through the Educational System in North-West England
