An Introduction to Optimal Designs for Social and Biomedical Research

DOI10.1002/9780470746912zbMath1182.62154OpenAlexW588037209MaRDI QIDQ3391610

Publication date: 12 August 2009

Full work available at URL: https://doi.org/10.1002/9780470746912

Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05) Applications of statistics to social sciences (62P25) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics (62-01)

Related Items

Information measures and design issues in the study of mortality deceleration: findings for the gamma-Gompertz model, Bayesian \(D\)-optimal designs for the two parameter logistic mixed effects model, The influence of a covariate on optimal designs in longitudinal studies with discrete-time survival endpoints, Maximin efficiencies under treatment-dependent costs and outcome variances for parallel, AA/BB, and AB/BA designs, Optimal experimental designs for accelerated failure time with Type I and random censoring, An algorithm based on semidefinite programming for finding minimax optimal designs, A class of optimization problems on minimizing variance based criteria in respect of parameter estimators of a linear model, Dynamic Programming for Response-Adaptive Dose-Finding Clinical Trials, Optimal item calibration for computerized achievement tests, R-optimal designs for multi-factor models with heteroscedastic errors, Minimax A‐, c‐, and I‐optimal regression designs for models with heteroscedastic errors, D‐optimal designs for a continuous predictor in longitudinal trials with discrete‐time survival endpoints, Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming‐Based Approach, Maximin design of cluster randomized trials with heterogeneous costs and variances, Optimal treatment allocation and study duration for trials with discrete-time survival endpoints, Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives, Constructing K-optimal designs for regression models, Optimal design of the Wilcoxon-Mann-Whitney-test, Continuous online item calibration: parameter recovery and item utilization, Adaptive grid semidefinite programming for finding optimal designs, Maximin and maximin-efficient event-related fMRI designs under a nonlinear model, Optimal design of longitudinal data analysis using generalized estimating equation models, Efficient sample size allocation with cost constraints for heterogeneous-variance group comparison, SamP2Cet: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials, Bayesian optimal cluster designs, Robust integer-valued designs for linear random intercept models, D-optimal designs based on the second-order least squares estimator, Optimal designs for the Rasch model, On the Choice of a Prior for Bayesian D-Optimal Designs for the Logistic Regression Model with a Single Predictor, A semi-infinite programming based algorithm for determining T-optimum designs for model discrimination, A permutational-splitting sample procedure to quantify expert opinion on clusters of chemical compounds using high-dimensional data, Robustness of Bayesian D-optimal design for the logistic mixed model against misspecification of autocorrelation, Using SeDuMi to find various optimal designs for regression models, Application of imperialist competitive algorithm to find minimax and standardized maximin optimal designs, A Metaheuristic Adaptive Cubature Based Algorithm to Find Bayesian Optimal Designs for Nonlinear Models, DUAL-OBJECTIVE OPTIMAL MIXTURE DESIGNS, A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs, Greedy active learning algorithm for logistic regression models, An exchange algorithm for optimal calibration of items in computerized achievement tests, Optimal Bayesian adaptive design for test-item calibration, D-optimal designs for beta regression models with single predictor, Optimal Designs for Multi-Response Nonlinear Regression Models With Several Factors via Semidefinite Programming, \(R\)-optimality criterion for regression models with asymmetric errors, Minimax robust designs for regression models with heteroscedastic errors, \(G\)-optimal designs for hierarchical linear models: an equivalence theorem and a nature-inspired meta-heuristic algorithm, On the information obtainable from comparative judgments, A semi-infinite programming based algorithm for finding minimax optimal designs for nonlinear models

Uses Software

fminsearch