| Quantifying efficiency gains of innovative designs of two-arm vaccine trials for COVID-19 using an epidemic simulation model |
529:B |
QCAS / 69 / 1-2 / 97 |
| The case-control approach can be more powerful for matched pair observational studies when the outcome is rare |
529:Y |
QCAS / 69 / 1-2 / 99 |
| Dose-finding designs and benchmark for right a censored endpoint |
529:Y |
QCAS / 68 / 1-2 / 99 |
| Use of alternative designs and data sources for pediatric trials |
529:B |
QCAS / 67 / 3-4 / 267 |
| Two-stage adaptive designs for three-treatment bioequivalence studies |
529:B |
QCAS / 66 / 5-6 / 419 |
| Bayesian uncertainty directed trial designs |
529:Y |
QCAS / 66 / 5-6 / 423 |
| Supersaturated multistratum designs |
529:Y |
QCAS / 66 / 5-6 / 425 |
| An integer linear programing approach to find trend-robust run orders of experimental designs |
529:Y |
QCAS / 66 / 1-2 / 101 |
| Trellis plots as visual aids for analyzing split plot experiments |
529:Y |
QCAS / 63 / 5-6 / 465 |
| A comparison of two-level designs to estimate all main effects and two factor interactions |
529:Y |
QCAS / 63 / 3-4 / 249 |
| The difference between “equivalent” and “not different” |
529:Y |
QCAS / 63 / 3-4 / 251 |
| Using design of experiments methods for applied computational fluid dynamics: A case study |
529:Y |
QCAS / 63 / 3-4 / 253 |
| A stratified two-stage unrelated randomized response model
for estimating a rare sensitive attribute based on the Poisson distribution |
529:Y |
QCAS / 63 / 3-4 / 255 |
| Two-level screening designs derived from binary nonlinear codes |
529:Y |
QCAS / 63 / 3-4 / 257 |
| Small mixed-level screening designs with orthogonal quadratic effects |
529:Y |
QCAS / 63 / 3-4 / 259 |
| Comparing two binary diagnostic tests with repeated measurements |
529:Y |
QCAS / 63 / 1-2 / 105 |
| A dose-schedule finding design for phase I-II clinical trials |
529:Y |
QCAS / 63 / 1-2 / 107 |
| Optimizing two-level supersaturated designs using swarm intelligence techniques |
529:Y |
QCAS / 63 / 1-2 / 109 |
| Generalizing quantile regression for counting process with
applications to recurrent events |
529:Y |
QCAS / 62 / 5-6 / 493 |
| Statistical monitoring of safety in clinical trials |
529:B |
QCAS / 62 / 4 / 361 |
| Optimal sliced Latin hypercube designs |
529:Y |
QCAS / 62 / 4 / 363 |
| Analysis of an unreplicated 22
factorial experiment
performed in a continuous process |
529:Y |
QCAS / 62 / 3 / 237 |
| Optimal designs for comparing curves |
529:Y |
QCAS / 62 / 3 / 239 |
| A case study in mixture design:
Multi response optimization of glaze formulation |
529:M |
QCAS / 62 / 1-2 / 105 |
| Some ideas on why factorial designs are seldom used for full-scale experiments in continuous production processes |
529:Y |
QCAS / 62 / 1-2 / 107 |
| Biased sampling designs to improve research efficiency: Factors
influencing pulmonary function over time in children with asthma |
529:B |
QCAS / 61 / 5-6 / 495 |
| A revisit to contingency table and test of independence:
Bootstrap is preferred to Chi-square approximations
as well as Fisher’s exact test |
529:Y |
QCAS / 61 / 5-6 / 499 |
| I-optimal design of mixture experiments in the presence
of ingredient availability constraints |
529:Y |
QCAS / 61 / 5-6 / 501 |
| A hybrid model for combining case–control
and cohort studies in systematic reviews of diagnostic tests |
529:Y |
QCAS / 61 / 4 / 377 |
| Higher order response-adaptive urn designs for clinical trials with highly successful treatments |
529:B |
QCAS / 61 / 1-2 / 103 |
| Extended mixed-level super
saturated designs |
529:Y |
QCAS / 61 / 1-2 / 107 |
| Model selection for estimating treatment effects |
529:B |
QCAS / 60 / 5-6 / 537 |
| Design-comparable effect sizes in multiple baseline designs:
A general modeling framework |
529:Y |
QCAS / 60 / 4 / 367 |
| The best location for speed bump installation using Taguchi
and classical design of experiments |
529:Y |
QCAS / 60 / 4 / 371 |
| Variable importance in matched case–control studies in settings of high dimensional data |
529:B |
QCAS / 60 / 3 / 251 |
| Proposed nonparametric test for the mixed two-sample design |
529:Y |
QCAS / 60 / 3 / 255 |
| Selecting a D-optimal follow-up experiment among candidate choices |
529:Y |
QCAS / 60 / 1-2 / 103 |
| Optimal designs for dose finding studies with an active control |
529:Y |
QCAS / 60 / 1-2 / 105 |
| A retrospective view of mixture experiments |
529:Y |
QCAS / 58 / 3 / 241 |
| Optimal semifoldover plans for two-level orthogonal designs |
529:Y |
QCAS / 58 / 1-2 / 97 |
| A case study involving mixture-process variable experiments
within a split-plot structure |
529:Y |
QCAS / 58 / 1-2 / 101 |
| Design of experiments for categorical repeated measurements
in packet communication networks |
529:Z |
QCAS / 58 / 1-2 / 103 |
| A Bayesian optimal design for accelerated degradation tests |
529:Y |
QCAS / 57 / 4 / 371 |
| Structural testing of 2×2 factorial effects: An analytic plan requiring fewer observations |
529:Y |
QCAS / 57 / 3 / 253 |
| Three-level and mixed-level orthogonal arrays for lean designs |
529:Y |
QCAS / 56 / 5-6 / 509 |
| Estimation and adjustment of bias in randomized evidence by using mixed treatment comparison meta-analysis |
529:Y |
QCAS / 56 / 1-2 / 111 |
| Analyzing designed experiments in distance sampling |
529:Y |
QCAS / 55 / 5-6 / 521 |
| A cluster analysis selection strategy for supersaturated designs |
529:Y |
QCAS / 55 / 4 / 373 |
| D-optimal designs with interaction coverage |
529:Y |
QCAS / 55 / 3 / 253 |
| Order statistics for a two-level, eight-run saturated- unreplicated fractional-factorial screening |
529:Y |
QCAS / 55 / 1-2 / 101 |
| Covariate balance in simple stratified and clustered comparative studies |
529:Y |
QCAS / 54 / 1-2 / 101 |
| The use of a supersaturated experiments in turbine engine development |
529:Y |
QCAS / 52 / 5 / 557 |
| Imputation of censored response data in a bivariate designed experiment |
529:Y |
QCAS / 52 / 5 / 559 |
| Further exploratory analysis of split-plot experiments to study certain stratified effects |
529:Y |
QCAS / 52 / 5 / 561 |
| Noise strategy in robust design: What aspects of noise factors are important in quality engineering? |
529:Y |
QCAS / 52 / 4 / 439 |
| Robust parameter design with feedback control |
529:Y |
QCAS / 52 / 4 / 441 |
| A nonparametric procedure for the analysis of balanced crossover designs |
529:Y |
QCAS / 51 / 6 / 665 |
| Construction of a 21-component layered mixture experiment design using a new mixture coordinate-exchange algorithm |
529:Y |
QCAS / 51 / 4 / 425 |
| A discussion of alternative ways of modeling and interpreting mixture data |
529:Y |
QCAS / 51 / 3 / 319 |
| Using genetic algorithms to generate mixture-process experimental designs involving control and noise variables |
529:Y |
QCAS / 50 / 4 / 441 |
| Multiresponse robust design: A general framework based on combined array |
529:Y |
QCAS / 49 / 5 / 563 |
| Retrospective factorial fitting and reverse design of experiments |
529:Y |
QCAS / 48 / 6 / 675 |
| Experimental designs for constrained regions |
529:Y |
QCAS / 48 / 5 / 555 |
| Optimal few-stage designs |
529:Y |
QCAS / 48 / 3 / 323 |
| Methods for selecting crossover designs with applications to an experiment with two factors in a split plot |
529:Y |
QCAS / 48 / 3 / 325 |
| Robust design: A simple alternative to Taguchi’s parameter design approach |
529:Y |
QCAS / 48 / 2 / 203 |
| Construction of orthogonal two-level designs of user-specified resolution where N ≠ 2k |
529:Y |
QCAS / 47 / 1 / 85 |
| Correlation in a Bayesian framework |
529:Y |
QCAS / 47 / 1 / 87 |
| On optimal third order rotatable designs |
529:Y |
QCAS / 47 / 1 / 91 |
| Phase I analysis for autocorrelated processes |
529:Y |
QCAS / 46 / 5 / 569 |
