CommentariesIncorrect analysis of crossover trials in animal behaviour research
References (76)
MULCOX2: a general computer program for the Cox regression analysis of multivariate failure time data
Computer Methods and Programs in Biomedicine
(1993)- et al.
The desirability of adjusting for residual effects in a crossover design
Biometrics
(1984) Categorical Data Analysis
(1990)Distribution-free fitting of logit models with random effects for repeated categorical responses
Statistics in Medicine
(1993)Longitudinal data analysis (repeated measures) in clinical trials
Statistics in Medicine
(1999)Statistical Methods in Biology
(1995)- et al.
Sampling and Statistical Methods for Behavioral Ecologists
(1998) - et al.
Marginal modeling of binary cross-over data
Biometrics
(1993) - et al.
A nonparametric approach to the analysis of three-treatment three-period crossover designs
Biometrika
(1995) Statistics for Biologists
(1989)
Modelling Survival Data in Medical Research
GLIM for Ecologists
Analysis of Repeated Measures
Anti-predator behaviour changes following an aggressive encounter in the lizard Tropidurus hispidus
Proceedings of the Royal Society of London, Series B
Analysis of Longitudinal Data
An Introduction to Generalized Linear Models
Crossover designs with correlated observations
Journal of Biopharmaceutical Statistics
Randomization Tests
A nonparametric approach to the analysis of the 2-treatment, 2-period, 4-sequence crossover model
Biometrics
A random effects model for ordinal responses from a crossover trial
Statistics in Medicine
A random effects model for ordinal responses from a crossover trial: Reply
Statistics in Medicine
Cross-over trials with censored data
Statistics in Medicine
Change-over clinical trial with binary data: mixed-model-based comparison of tests
Biometrics
General class of covariance structures for two or more repeated factors in longitudinal data analysis
Communications in Statistics. Theory and Methods
Analysis of crossover designs with multivariate response
Statistics in Medicine
Estimating treatment effects in clinical crossover trials
Journal of Biopharmaceutical Statistics
Some analysis strategies for three-period changeover designs with two treatments
Statistics in Medicine
Review of software to fit Generalized Estimating Equation regression models
American Statistician
Analysis of Multivariate Survival Data
Multivariate nonparametric analysis for the two-period crossover design with application in clinical trials
Journal of Biopharmaceutical Statistics
Analyzing multivariate data in crossover designs using permutation tests
Journal of Biopharmaceutical Statistics
Modelling and design of cross-over trials
Statistics in Medicine
Design and Analysis of Cross-Over Trials
Comments on ‘Estimating treatment effects in clinical crossover trials’
Journal of Biopharmaceutical Statistics
Multivariate non-parametric methods for Mann-Whitney statistics to analyse cross-over studies with two treatment sequences
Statistics in Medicine
The Statistical Analysis of Failure Time Data
The analysis of binary and categorical data from crossover trials
Statistical Methods in Medical Research
Cited by (62)
Randomised controlled trial of corneal vs. scleral rigid gas permeable contact lenses for keratoconus and other ectatic corneal disorders
2020, Contact Lens and Anterior EyeCitation Excerpt :In a crossover design the analysis should take account of the period and sequence effects, which may be confounded with treatment effects, [53,54]. It is reasonable to assume that randomisation minimises sequence effects: the period effect must be accounted for due to possible changes of the participants during the intervals between the measurements, or through habituation to the measurement itself [55]. The possibility of a differential carryover effect must also be accounted for, although it is unlikely in chronic conditions such as keratoconus, under non-curative management, such as contact lenses and with the incorporation of a washout period [53,54].
Combined effects of nocturnal exposure to artificial light and habitat complexity on fish foraging
2019, Science of the Total EnvironmentCitation Excerpt :Hence, only the disturbed light cycle treatments were used for behavioural analyses. To determine factors affecting fish consumption (log-transformed numbers of consumed gammarids) we applied a General Linear Mixed Model (GLMM) for cross-over designs as per Díaz-Uriarte (2002) and Jones and Kenward (2003). The following factors were included in the model: (1) ‘Light cycle’, a between-subject fixed factor indicating the presence or absence of artificial light at night; (2) ‘Habitat type’, a between-subject fixed factor indicating a habitat type (sandy substratum or woody debris); (3) ‘Period’, a within-subject fixed factor adjusted for time of the day, indicating the first or second period during each trial (to show the effect of passing time on fish responses); (4) ‘Sequence’, a between-subject fixed factor referring to the sequence of periods (dusk/night or night/dusk); (5) ‘Time of the day’, a within-subject fixed factor adjusted for period (dusk or night) and (6) fish individual as a random factor.
Binary patch assessment by goldfish under safe and dangerous conditions
2018, Behavioural ProcessesCortisol during adolescence organises personality traits and behavioural syndromes
2018, Hormones and Behavior
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Correspondence and present address: R. Dı́az-Uriarte, Navacerrada 37, 28430 Alpedrete, Madrid, Spain (email:[email protected] ).