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Background: Quantitative research designs are broadly classified as being either experimental or quasi-experimental. Factorial designs are a form of experimental design and enable researchers to examine the main effects of two or more independent variables simultaneously. They also enable researchers to detect interactions among variables. Aim: To present the features of factorial designs. Discussion: This article provides an overview of the factorial design in terms of its applications, design features and statistical analysis, as well as its advantages and disadvantages. Conclusion: Factorial designs are highly efficient for simultaneously evaluating multiple interventions and present the opportunity to detect interactions amongst interventions. Such advantages have led researchers to advocate for the greater use of factorial designs in research when participants are scarce and difficult to recruit. Implications for practice: A factorial design is a cost-effective way to determine the effects of combinations of interventions in clinical research, but it poses challenges that need to be addressed in determining appropriate sample size and statistical analysis. [ABSTRACT FROM AUTHOR]

Background Quantitative research designs are broadly classified as either experimental or quasi-experimental. The main distinguishing feature of the quasi-experiment is the manipulation of the independent variable without randomisation. When randomisation or use of a control group is unfeasible, a researcher can choose from a range of quasi-experimental designs. Aim To present the features of the quasi-experimental 'non-equivalent control group post-test-only' design, which aims to demonstrate causality between an intervention and an outcome. Discussion This paper provides an overview of the non-equivalent control group post-test-only design in terms of its design features, applications and statistical analysis, as well as its advantages and disadvantages. Conclusion The non-equivalent control group post-test-only design can be used in natural settings, where randomisation cannot be conducted for ethical or practical reasons. Although the design is less complex than some other designs, with low error propagation, it is vulnerable to threats to internal validity. [ABSTRACT FROM AUTHOR]

Background: Quantitative research designs are broadly classified as either experimental or quasi-experimental. The main distinguishing feature of the quasi-experiment is the manipulation of the independent variable without randomisation. When randomisation or use of a control group is unfeasible, a researcher can choose from a range of quasi-experimental designs., Aim: To present the features of the quasi-experimental 'non-equivalent control group post-test-only' design, which aims to demonstrate causality between an intervention and an outcome., Discussion: This paper provides an overview of the non-equivalent control group post-test-only design in terms of its design features, applications and statistical analysis, as well as its advantages and disadvantages., Conclusion: The non-equivalent control group post-test-only design can be used in natural settings, where randomisation cannot be conducted for ethical or practical reasons. Although the design is less complex than some other designs, with low error propagation, it is vulnerable to threats to internal validity., Competing Interests: None declared, (©2018 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.)