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- Andrew Gelman, Iain Pardoe
- Technometrics
- 2006

Explained variance (R2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models that we consider inâ€¦ (More)

- Andrew Gelman, Iain Pardoe
- 2007

In a predictive model, what is the expected difference in the outcome associated with a unit difference in one of the inputs? In a linear regression model without interactions, this averageâ€¦ (More)

- Iain Pardoe, Xiangrong Yin, R. Dennis Cook
- Technometrics
- 2007

Sufficient dimension reduction methods provide effective ways to visualize discriminant analysis problems. For example, Cook and Yin (2001) showed that the dimension reduction method of slicedâ€¦ (More)

- Iain Pardoe, Charles H. Lundquist
- 2002

Before a logistic regression model is used to describe the relationship between a binary response variable and predictors, the fit of the model should be assessed. The nature of any model deficiencyâ€¦ (More)

- Iain Pardoe
- 2002

A necessary step in any regression analysis is checking the fit of the model to the data. Graphical methods are often employed to allow visualization of features that the data should exhibit if theâ€¦ (More)

This report presents (1) the basic ideas of bootstrapping when applied in regression problems, as described in [2, 3], and (2) how to implement these ideas using Arc, the computer package thatâ€¦ (More)

- Oliver Dain, Matthew L. Ginsberg, +4 authors Iain Pardoe
- Proceedings of the 2006 Winter Simulationâ€¦
- 2006

SimYard is a stochastic shipyard simulation tool designed to evaluate the labor costs of executing different schedules in a shipyard production environment. SimYard simulates common productionâ€¦ (More)

- Iain Pardoe, Catherine A. Durham, Charles H. Lundquist
- 2003

Standard model assessment techniques such as residual plots or Akaikeâ€™s information criterion can be difficult to use or provide limited insight into model fit when applied in non-standard regressionâ€¦ (More)

Average predictive effects for models with nonlinearity , interactions , and variance components âˆ—

- Andrew Gelman, Iain Pardoe
- 2004

In a predictive model, what is the expected change in the outcome associated with a unit change in one of the inputs? In a linear regression model without interactions, this average predictive effectâ€¦ (More)

- Oliver Dain, Matthew L. Ginsberg, +4 authors Andrew Stoneman
- 2005

TheARGOSscheduling system is designed to reduce labor costs in large facilities such as shipyards. Theoretical results suggest that ARGOS is capable of reducing total labor costs for a large shipâ€¦ (More)