Inferential studies to investigate the health of rare, exotic, or companion animals are often challenging because sample groups of sufficiently large sizes are difficult to obtain. This may be a result of limited availability of exotic or endangered animals or the ethical desire to limit the number of animals involved in painful or terminal studies. In standard study designs with adequate statistical power, the number of animals required for inclusion is often greater than the number that can be obtained or feasibly managed. Also, the cost of providing long-term care for research animals is often greater than the available funding for research in animal health. The purpose of this article is to provide an overview of single-case study designs and analyses and outline how these types of analyses may be used for animal studies when conditions warrant the use of a single subject.
Specific statistical methods and study designs have been developed for use when very few subjects are available; the latter are known as small N study designs (where N represents the number of study subjects) or single-case study designs when 1 study subject is used. These study designs were developed primarily in the field of human behavioral science1,2 and were used to monitor and evaluate patients and clinical practice.3 Sometimes, the characteristics of an individual patient (eg, age, sex, or disease status) may not match the inclusion criteria of published research projects that evaluate treatment options. In such situations, the proponents of evidence-based medicine have suggested using single-case designs to assess treatment effects for a particular patient.4 Single-case study designs are also called single-subject or single-system designs. The latter term may be useful when applying the method to an agglomeration of units that are treated as an entity, such as a litter, herd, farm, or production facility. For convenience in this article, we use the term subject or single case to refer to an individual animal and an aggregation of animals that is treated as an entity.
Single-case designs are used to assess a subject over time (ie, before, during, or after 1 or more interventions such as surgical, medical, and behavioral treatments or biosecurity measures). Usually, the subject is also assessed during a postintervention follow-up period. The idea behind the design is to collect enough data to allow statistical comparisons among the different phases of treatment; the intent is to determine whether a change in the course of a medical problem was a consequence of the intervention rather than chance. The data analysis must take into consideration the repeated-measures (ie, autocorrelated) aspect of the data, which may induce correlation among the observations.
There are arguments for and against the use of single-case designs in research. Group-based methods provide inference for a supposedly typical subject, but single-case designs infer the effect of treatment on a single subject. Therefore, with regard to provision of study results that can be generalized to a population, single-case designs cannot replace classical designs. Nevertheless, single-case designs are longitudinal and provide insight into the disease process and the effect of medical intervention over time.
Single-case study designs are members of a large class of statistical designs known as quasi-experiments. Quasi-experiments typically lack 1 or more features (eg, control groups, randomization, or causal hypotheses) of a complete experiment. However, quasi-experiments have been widely used to identify trends or develop hypotheses in scientific fields such as criminal justice and behavioral sciences, for which subject characteristics or ethical issues make it difficult to perform a traditional experiment. Single-case designs and analyses differ from case study reports in that they provide quantitative, inferential information about disease processes and interventions, which is important for the medical community and not available in a case study report.
In some research (eg, kinetic studies), the temporal process of the disease process is known or expected. The objective of such a study is to assess features of the data attributable to the physiologic process that are affected by interventions.
In this review, we begin with a description of designs for single-case experiments, followed by a discussion of the baseline and intervention phases. Data analyses appropriate for single-case designs are outlined, and a description of a single-case experiment to assess variation in the gait of an emu is provided; the latter is further discussed, as are single-case study designs in general.
Peak vertical force
Ground reaction force
Generalized estimating equation
Reinisch D, Conzemius M. The effect of human interaction on behavioral adaptations in the emu chick. Poster presentation, NIH summer scholars program, 2003.
S-Plus, Mathsoft Inc, Seattle, Wash.
Sackett DLStraus SRichardson S, et al.Evidence-based medicine: how to practice and teach EBM. 2nd ed. New York: Churchill Livingstone Inc, 2000.
Todman JDugard P. Single-case and small-n experimental designs: a practical guide to randomization tests. Mahwah, NJ: Lawrence Erlbaum, 2001.
Conzemius MGBrown TDZhang Y, et al.A new animal model of femoral head osteonecrosis: one that progresses to human-like mechanical failure. J Orthop Res 2002; 20: 303–309.
Rumph PFSteiss JEWest MS, et al.Interday variation in vertical ground reaction force in clinically normal Greyhounds at the trot. Am J Vet Res 1999; 60: 679–683.
Conzemius MGEvans RBBesancon MF, et al.Effect of surgical technique on limb function after surgery for rupture of the cranial cruciate ligament in dogs. J Am Vet Med Assoc 2005; 226: 232–236.
Kuehl RO. Design of experiments: statistical principles of research design and analysis. Pacific Grove, Calif: Duxbury Press, 2000.