Random effects models for complex designs.

Plaid designs are characterised by having one set of treatments applied to rows and another set of treatments applied to columns. In a 2003 publication, Farewell and Herzberg presented an analysis of variance structure for such designs. They presented an example of a study in which medical practitioners, trained in different ways, evaluated a series of videos of patients obtained under a variety of conditions. However, their analysis did not take full account of all error terms. In this paper, a more comprehensive analysis of this study is presented, informed by the recognition that the study can also be regarded as a two-phase design. The development of random effects models is outlined and the potential importance of block-treatment interactions is highlighted. The use of a variety of techniques is shown to lead to a better understanding of the study. Examination of the variance components involved in the expected mean squares is demonstrated to have particular value in identifying appropriate error terms for F-tests derived from an analysis of variance table. A package such as ASReml can also be used provided an appropriate error structure is specified. The methods presented can be applied to the design and analysis of other complex studies in which participants supply multiple measurements under a variety of conditions.

SARS incubation and quarantine times: when is an exposed individual known to be disease free?

The setting of a quarantine time for an emerging infectious disease will depend on current knowledge concerning incubation times. Methods for the analysis of information on incubation times are investigated with a particular focus on inference regarding a possible maximum incubation time, after which an exposed individual would be known to be disease free. Data from the Hong Kong SARS epidemic are used for illustration. The incorporation of interval-censored data is considered and comparison is made with percentile estimation. Results suggest that a wide class of models for incubation times should be considered because the apparent informativeness of a likelihood depends on the choice and generalizability of a model. There will usually remain a probability of releasing from quarantine some infected individuals and the impact of early release will depend on the size of the epidemic.

Acute cervical spinal cord injury secondary to air bag deployment without proper use of lap or shoulder harnesses.

The authors present a case report of a patient with cervical central spinal cord syndrome caused by a hyperextension injury after a motor vehicle collision in which the air bag deployed in the absence of shoulder or lap belt harnesses. The potential for cervical spine and spinal cord hyperextension injuries in passengers positioned in front of air bags without proper use of shoulder or lap belt harnesses is discussed. Cervical central spinal cord quadriplegia occurred with cervical spondylosis and kyphosis that was managed by early three-level cervical corpectomy in a 58-year-old patient. Early improvement in the patient's neurological status occurred but was incomplete at the time of this report. Cervical hyperextension injuries are possible in passengers positioned in the front seat of cars with air bags when shoulder or lap belt harnesses are not used properly. Previous biomechanical studies have documented the potential for these types of injuries.

Incomplete factorial designs for randomized clinical trials.

Recently there has been increased interest in considering factorial designs for randomized clinical trials when one wishes to study two or more treatments. Such designs may offer impressive gains in efficiency compared with a series of trials studying one treatment at a time. This is especially true when the treatments do not interact with one another. If interactions are of special interest, factorial designs provide one sensible approach for studying them, but larger sample sizes would be required because tests for interactions have lower power than those for main effects. In trials designed to test putative agents for preventing cancer, interactions may be of less interest so that fractions of higher-order factorial designs might be appropriate. Sometimes it may not be reasonable, interesting, feasible, or ethical to study all treatment combinations required in a complete or fractional factorial design, yet one may want to preserve some of the factorial structure to increase efficiency and to aid understanding. For such situations, incomplete factorial designs are proposed. Although not all of the advantages of full factorial designs are preserved, such designs may provide reasonable compromises for certain situations.

Optimum experimental designs for properties of a compartmental model.

Three properties of interest in bioavailability studies using compartmental models are the area under the concentration curve, the maximum concentration, and the time to maximum concentration. Methods are described for finding designs that minimize the variance of the estimates of these quantities in such a model. These methods use prior information. Both prior estimates and prior distributions are used. The designs for an open one-compartment model are compared with the corresponding D theta-optimum design for all parameters and also with designs that minimize the sum of the scaled variances of the individual properties.

Cage allocation designs for rodent carcinogenicity experiments.

Cage allocation designs for rodent carcinogenicity experiments are discussed and presented with the goal of avoiding dosage group biases related to cage location. Considerations in selecting a cage design are first discussed in general terms. Specific designs are presented for use in experiments involving three, four, and five dose groups and with one, four, and five rodents per cage. Priorities for balancing treatment groups include horizontal position on shelf and shelf of rack, nearest neighbor balance, and male-female balance. It is proposed that these balance criteria be considered together with practical issues, such as the ability to accurately conform to a design and to determine a sensible and efficient design for each experiment.

Cage allocation designs for rodent carcinogenicity experiments.

Cage allocation designs for rodent carcinogenicity experiments are discussed and presented with the goal of avoiding dosage group biases related to cage location. Considerations in selecting a cage design are first discussed in general terms. Specific designs are presented for use in experiments involving three, four, and five dose groups and with one, four, and five rodents per cage. Priorities for balancing treatment groups include horizontal position on shelf and shelf of rack, nearest neighbor balance, and male-female balance. It is proposed that these balance criteria be considered together with practical issues, such as the ability to accurately conform to a design and to determine a sensible and efficient design for each experiment.