Jian Bi

发表

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews

C. Kuesten, Jian Bi, 2018, Foods.

Computer-intensive methods for sensory data analysis, exemplified by Durbin's rank test.

Jian Bi, 2009 .

THE BETA‐BINOMIAL MODEL: ACCOUNTING FOR INTER‐TRIAL VARIATION IN REPLICATED DIFFERENCE AND PREFERENCE TESTS

D. Ennis, Jian Bi, 1998 .

A REVIEW OF STATISTICAL METHODS FOR DETERMINATION OF RELATIVE IMPORTANCE OF CORRELATED PREDICTORS AND IDENTIFICATION OF DRIVERS OF CONSUMER LIKING

Jian Bi, 2012 .

IDENTIFICATION OF DRIVERS OF OVERALL LIKING – DETERMINATION OF RELATIVE IMPORTANCES OF REGRESSOR VARIABLES

Jian Bi, Julia Chung, J. Chung, 2011 .

Jian Bi, Jian Bi, 2005 .

DIFFICULTIES AND A WAY OUT: A BAYESIAN APPROACH FOR SENSORY DIFFERENCE AND PREFERENCE TESTS

Jian Bi, 2003 .

A THURSTONIAN MODEL AND STATISTICAL INFERENCE FOR THE 2-ALTERNATIVE CHOICE TEST WITH BOTH TEST PAIRS AND PLACEBO PAIRS

Jian Bi, Hye-Seong Lee, Michael O'Mahony, 2015 .

Analyzing consumers’ Profile of Mood States (POMS) data using the proportional odds model (POM) for clustered or repeated observations and R package ‘repolr’

H. Meiselman, C. Kuesten, Jian Bi, 2017 .

Jian Bi, 2007 .

SENSORY THRESHOLDS: CONCEPTS AND METHODS

Jian Bi, Daniel M. Ennis, D. Ennis, 1998 .

Paired versions of various sensory discrimination forced-choice methods and the same-different area theorem

M. O'Mahony, C. Kuesten, Jian Bi, 2018 .

Estimating population or group sensitivity and its precision from a set of individual d'.

Jian Bi, 2005, The British journal of mathematical and statistical psychology.

Propensity score analysis (PSA) for sensory causal inference – Global consumer psychographics and applications for phytonutrient supplements

H. Meiselman, C. Kuesten, Jian Bi, 2016 .

Risk Assessment of Negative Sensory Effects in Product Development Using the Benchmark Dose (BMD) Methodology for Continuous Data

C. Kuesten, Jian Bi, 2015 .

A new form of the psychometric function for the unspecified tetrad

Jian Bi, 2020 .

A THURSTONIAN VARIANT OF THE BETA‐BINOMIAL MODEL FOR REPLICATED DIFFERENCE TESTS

D. Ennis, Jian Bi, 1998 .

Type I error, testing power, and predicting precision based on the GLM and LM models for CATA data--Further discussion with M. Meyners and A. Hasted

C. Kuesten, Jian Bi, 2023, Food Quality and Preference.

Variance of d′ for the Tetrad Test and Comparisons with Other Forced‐Choice Methods

M. O'Mahony, Jian Bi, 2013 .

HOW TO ESTIMATE AND USE THE VARIANCE OF d’ FROM DIFFERENCE TESTS

Jian Bi, Daniel M. Ennis, Michael O'Mahony, 1997 .

Estimating and Testing Parameters of the Thurstonian Model for Torgerson's Method of Triads

C. Kuesten, Jian Bi, 2015 .

STATISTICAL MODELS FOR THE A-NOT A METHOD

D. Ennis, Jian Bi, 2001 .

STATISTICAL ANALYSES FOR R‐INDEX

Jian Bi, 2006 .

Sparse hierarchical clustering based on Menopause Rating Scale severity of symptoms collected from perimenopausal and postmenopausal US women in a menopause tablet perceptual efficacy study

C. Kuesten, Jian Bi, Jennifer Dang, 2023, Journal of Sensory Studies.

Japanese consumer segmentation based on general self-efficacy psychographics data collected in a phytonutrient supplement study: Influence on health behaviors, well-being, product involvement and liking

H. Meiselman, C. Kuesten, Jian Bi, 2022, Food Quality and Preference.

INTRACLASS CORRELATION COEFFICIENT (ICC): A FRAMEWORK FOR MONITORING AND ASSESSING PERFORMANCE OF TRAINED SENSORY PANELS AND PANELISTS

Carla Kuesten, Jian Bi, C. Kuesten, 2012 .

The Use of Demographics and Psychographics to Study Product Effects with Nutrient Supplements: Exploratory Multi-Country Data

H. Meiselman, C. Kuesten, Jian Bi, 2021, Foods.

Case studies of industrial applications of the “M+N” classification method with larger M and N for visual and manual inspections

Jian Bi, Carla Kuesten, Amy Hou, 2017 .

Revisiting Fisher’s ‘Lady Tasting Tea’ from a perspective of sensory discrimination testing

Jian Bi, Carla Kuesten, C. Kuesten, 2015 .

THE DIRICHLET‐MULTINOMIAL MODEL: ACCOUNTING FOR INTER‐TRIAL VARIATION IN REPLICATED RATINGS

Jian Bi, Daniel M. Ennis, D. Ennis, 1999 .

Application of a panel performance reliability versus product effect size (PR-ES) framework: A protein powder case study

Jian Bi, Carla Kuesten, C. Kuesten, 2021 .

UPDATED AND EXTENDED TABLE FOR TESTING THE SIGNIFICANCE OF THE R-INDEX

M. O'Mahony, Jian Bi, 2007 .

Jian Bi, Jian Bi, 2011 .

d′ and variance of d′ for four-alternative forced choice (4-AFC).

M. O'Mahony, Jian Bi, H. Lee, 2010 .

Sensory Discrimination Tests and Measurements: Statistical Principles, Procedures and Tables

Jian Bi, Jian Bi, 2006 .

AGREEMENT AND RELIABILITY ASSESSMENTS FOR PERFORMANCE OF SENSORY DESCRIPTIVE PANEL

Jian Bi, Jian Bi, 2003 .

Review and development of Thurstonian models for the triangle and duo‐trio methods and paired versions of the methods

C. Kuesten, Jian Bi, 2020 .

BAYESIAN APPROACH TO SENSORY PREFERENCE, DIFFERENCE AND EQUIVALENCE TESTS

Jian Bi, 2011 .

Using the benchmark dose (BMD) methodology to determine an appropriate reduction of certain ingredients in food products.

Jian Bi, 2010, Journal of food science.

The performance of the dual reference duo-trio (DRDT) method using a balanced-reference mode

M. O'Mahony, Jian Bi, H. Lee, 2016 .

A global study using PANAS (PA and NA) scales to measure consumer emotions associated with aromas of phytonutrient supplements

H. Meiselman, C. Kuesten, Jian Bi, 2014 .

Replicated difference and preference tests: how to account for inter-trial variation

John M. Ennis, D. Ennis, Jian Bi, 2000 .

BETA‐BINOMIAL TABLES FOR REPLICATED DIFFERENCE AND PREFERENCE TESTS

D. Ennis, Jian Bi, 1999 .

THE POWER OF SENSORY DISCRIMINATION METHODS USED IN REPLICATED DIFFERENCE AND PREFERENCE TESTS

Jian Bi, Daniel M. Ennis, D. Ennis, 1999 .