Replication or exploration? Sequential design for stochastic simulation experiments |
520:Y |
QCAS / 66 / 1-2 / 95 |

Response modeling approach to robust parameter design methodology using supersaturated designs |
520:Y |
QCAS / 65 / 1-2 / 89 |

Reliability improvement of diamond drill bits using design of experiments |
520:Y |
QCAS / 65 / 1-2 / 93 |

Analyzing two-stage experiments in the presence of
Interference |
520:Y |
QCAS / 64 / 5-6 / 467 |

Considerations on testing secondary endpoints in group sequential design |
520:Y |
QCAS / 64 / 3-4 / 263 |

Optimal designs for dose response curves with common parameters |
520:Y |
QCAS / 64 / 3-4 / 265 |

Partial replication of small two-level factorial designs |
520:Y |
QCAS / 64 / 1-2 / 105 |

Bayesian design of experiments for generalized linear models
and dimensional analysis with industrial and scientific application |
520:Y |
QCAS / 63 / 5-6 / 457 |

Confirmation runs in design of experiments |
520:Y |
QCAS / 63 / 3-4 / 239 |

Identifying the structure of the experimental design |
520:Y |
QCAS / 63 / 3-4 / 243 |

An experimental diagnostic procedure to identify the source of defects in multi-stage and multi-component production processes |
520:Y |
QCAS / 63 / 3-4 / 245 |

Optimal designs for quadratic regression with random block effects: The case of block size two |
520:Y |
QCAS / 63 / 3-4 / 247 |

Process optimization through designed experiments to achieve
consistency in output color of a compounded plastic grade |
520:M |
QCAS / 61 / 4 / 375 |

Universally optimal designs for two interference models |
520:Y |
QCAS / 61 / 3 / 253 |

Dynamic Bayesian analysis for irregularly and incompletely
observed contingency tables |
520:Y |
QCAS / 59 / 5-6 / 507 |

A framework for initial experimental design in the presence of competing prior knowledge |
520:Y |
QCAS / 59 / 5-6 / 509 |

On estimating the mean of the selected normal population in two-stage adaptive designsller Title: please update |
520:Y |
QCAS / 59 / 4 / 359 |

Methods for planning repeated measures degradation studies |
520:Y |
QCAS / 59 / 3 / 243 |

Sequential estimation for covariate-adjusted response-adaptive designs |
520:Y |
QCAS / 59 / 1-2 / 125 |

Three-stage industrial strip-plot experiments |
520:Y |
QCAS / 59 / 1-2 / 127 |

Experimental designs for identifying casual mechanisms |
520:Y |
QCAS / 59 / 1-2 / 129 |

A Bayesian nonparametric model for Taguchi’s on-line quality monitoring procedure for attributes |
520:Y |
QCAS / 58 / 5-6 / 537 |

Designed experiments for the defense community |
520:Y |
QCAS / 58 / 4 / 361 |

Data transformations with a full 26 experimental design: A metal-cutting case study |
520:Y |
QCAS / 58 / 4 / 363 |

Fraud in clinical trials: Detecting it and preventing it |
520:B |
QCAS / 58 / 3 / 233 |

Optimum design of experiments for statistical inference |
520:Y |
QCAS / 58 / 3 / 235 |

Optimization of designed experiments based on multiple
criteria utilizing a Pareto frontier |
520:Y |
QCAS / 58 / 1-2 / 85 |

Simulated annealing model search for subset selection in screening experiments |
520:Y |
QCAS / 58 / 1-2 / 87 |

Some inferential procedures in randomized repeated measurement design for binary response |
520:Y |
QCAS / 58 / 1-2 / 89 |

Multi-treatment optimal response-adaptive designs for phase
III clinical trials |
520:Y |
QCAS / 58 / 1-2 / 91 |

Optimal process adjustment by integrating production data
and design of experiments |
520:Y |
QCAS / 57 / 5-6 / 519 |

A class of three-level designs for definitive screening in the presence of second-order effects |
520:Y |
QCAS / 57 / 4 / 365 |

Designing simulation experiments with controllable and uncontrollable factors for applications in healthcare |
520:Y |
QCAS / 57 / 4 / 367 |

Don’t use rank sum tests to analyze factorial designs |
520:Y |
QCAS / 57 / 4 / 369 |

Screening for fuel economy: A case study of supersaturated designs in practice |
520:Y |
QCAS / 57 / 3 / 241 |

A split-plot experiment with factor-dependent whole-plot sizes |
520:Y |
QCAS / 57 / 3 / 243 |

A class of three level designs for definite screening in the presence of second-order effects |
520:Y |
QCAS / 57 / 3 / 247 |

Exchange algorithms for constructing model robust experimental designs |
520:Y |
QCAS / 57 / 3 / 249 |

Optimal and efficient cross-over designs for test control study when subject efforts are random |
520:Y |
QCAS / 57 / 3 / 251 |

Why is not design of experiments widely used by engineers in Europe? |
520:A |
QCAS / 57 / 1-2 / 93 |

A Bayesian approach for integration of physical and computer experiments for quality improvement in nano-composite manufacturing |
520:M |
QCAS / 57 / 1-2 / 95 |

An estimated-score approach for dealing with missing covariate data in matched case-control studies |
520:Y |
QCAS / 57 / 1-2 / 97 |

D-optimal and D-efficient equivalent-estimation second-order split-plot designs |
520:Y |
QCAS / 57 / 1-2 / 99 |

Optimal row–column designs in high-throughput screening experiments |
520:Y |
QCAS / 57 / 1-2 / 101 |

A covariate-adjusted adaptive design for two-stage clinical trials with survival data |
520:Y |
QCAS / 56 / 1-2 / 105 |

Uncertainty in designed experiments |
520:Y |
QCAS / 56 / 1-2 / 107 |

Optimum designs versus orthogonal arrays for main effects and two-factor interactions |
520:Y |
QCAS / 55 / 5-6 / 509 |

Bayesian optimal design for change point problems |
520:Y |
QCAS / 55 / 5-6 / 511 |

Sensitivity analysis of optimal designs for accelerated life testing |
520:Y |
QCAS / 55 / 5-6 / 513 |

Using DEA’s multi-choice method to reach multi-response optimization in Taguchi’s Problem |
520:Y |
QCAS / 55 / 4 / 369 |

Proposed tests for the non-decreasing alternative in a mixed design |
520:Y |
QCAS / 55 / 4 / 371 |

Designed experiments with fixed and varying factors – A cautionary tale |
520:Y |
QCAS / 55 / 1-2 / 85 |

Deciphering all those minimum aberration criteria for experimental designs |
520:Y |
QCAS / 55 / 1-2 / 87 |

Formulating mixed models for experiments, including longitudinal experiments |
520:Y |
QCAS / 55 / 1-2 / 89 |

Marginally restricted D-optimal designs for correlated observations |
520:Y |
QCAS / 55 / 1-2 / 93 |

Analysis of data from non-orthogonal multistratum designs in industrial experiments |
520:Y |
QCAS / 55 / 1-2 / 95 |

A designed screening study with prespecified combinations of factor settings |
520:Y |
QCAS / 55 / 1-2 / 97 |

Modeling of Taguchi’s signal-to-noise ratios for healthcare |
520:B |
QCAS / 54 / 4 / 353 |

Product and process optimization through design of experiments: A case study |
520:Y |
QCAS / 54 / 3 / 239 |

Follow-up designs to resolve confounding in split-plot experiments |
520:Y |
QCAS / 54 / 3 / 241 |

Making tradeoffs in designing scientific experiments: A case study with multi-level factors |
520:Y |
QCAS / 54 / 3 / 243 |

A post-fractionated strip-strip-block design for multi-stage processes |
520:Y |
QCAS / 54 / 3 / 245 |

Analysis of optimization experiments |
520:Y |
QCAS / 54 / 1-2 / 97 |

Bayesian inference and life testing plan for the Weibull distribution in presence of progressive censoring |
520:Y |
QCAS / 54 / 1-2 / 99 |

Optimal designs for conjoint experiments |
520:Y |
QCAS / 53 / 6 / 591 |

A running example for use in a class on design of experiments |
520:Y |
QCAS / 53 / 4-5 / 457 |

Must a process be in statistical control before conducting designed experiments |
520:Y |
QCAS / 53 / 4-5 / 459 |

Randomization of neighbor balanced generalized Youden designs |
520:Y |
QCAS / 52 / 6 / 661 |

An experiment to compare Taguchi’s product array and the combined array |
520:Y |
QCAS / 52 / 5 / 537 |

The decomposition of effects in full factorial experimental design into individual treatment combinations |
520:Y |
QCAS / 52 / 5 / 539 |

Bayes optimal sequential trial designs |
520:Y |
QCAS / 52 / 5 / 541 |

Design of experiment algorithms for assembled products |
520:Y |
QCAS / 52 / 3 / 319 |

Efficient 2k factorial designs for blocks of size 2 with microarray applications |
520:Y |
QCAS / 52 / 3 / 325 |

One- and two-sided tolerance intervals for general balanced mixed models and unbalanced one-way random models |
520:Y |
QCAS / 52 / 2 / 211 |

New frontiers in the design of experiments |
520:Y |
QCAS / 52 / 1 / 79 |

Identifying need for new factors in EVOP |
520:Y |
QCAS / 51 / 6 / 663 |

Response modeling methodology (RMM) – maximum likelihood estimation procedures |
520:Y |
QCAS / 51 / 5 / 553 |

A game theory application in robust design |
520:Y |
QCAS / 51 / 4 / 421 |

A new approach for multiple-response optimization |
520:Y |
QCAS / 51 / 3 / 309 |

Large factorial designs for product engineering and marketing research applications |
520:Y |
QCAS / 51 / 3 / 311 |