Irrespective of whether there is an interaction, follow-up tests can be performed to determine in more detail how the within-subjects factors affected back pain. However, the order in which they receive this differs, with the 200 employees being randomly split into two groups: (a) 100 packers first undergo the control and then the treatment, whilst (b) the other 100 packers start with the treatment and then undergo the control (i.e., this is known as counterbalancing and helps to reduce the bias that could result from the order in which a condition is provided).Īt the end of the experiment, the retailer uses a two-way repeated measures ANOVA to determine whether any change in productivity (i.e., the dependent variable) is the result of the interaction between the use of music (i.e., the "conditions", which is one of our factors) and "time" (i.e., our second factor). Therefore, the dependent variable is "productivity" (measured in terms of the average number of packages fulfilled), whilst the two factors are the "conditions" (i.e., two groups: "control" or "treatment") and "time" (i.e., productivity at three time points, which are our three groups: "at the beginning of the experiment", "1 week later" and "4 weeks later").Īll 200 employees undergo the treatment and control. However, the retailer also wants to know whether any possible increase in productivity is affected by the time that the music is played (i.e., if there was an increase in productivity when music was provided, is this a long-term increase or perhaps only due to initial novelty?). Therefore, 200 packers take part in the experiment, which has a "control", where "no music" is played, and a "treatment", where "music" is played. The retailer wants to find out whether providing the packers with background music improves productivity.
Imagine that an online retailer wants to improve productivity amongst packers in their order fulfillment centre. However, the order in which they receive this differs, with the 30 employees being randomly split into two groups: (a) 15 participants first undergo treatment A and then treatment B, whilst (b) the other 15 participants start with treatment B and then undergo treatment A (i.e., this is known as counterbalancing and helps to reduce the bias that could result from the order in which a condition is provided).Īt the end of the experiment, the researcher uses a two-way repeated measures ANOVA to determine whether any change in back pain (i.e., the dependent variable) is the result of the interaction between the "type of treatment" (i.e., the massage programme or acupuncture programme, which is one of our two factors) and "time" (i.e., our second factor). Therefore, the dependent variable is "back pain", whilst the two factors are the "conditions" (i.e., two groups: "treatment A", the massage programme, and "treatment B", the acupuncture programme) and "time" (i.e., back pain at three time points, which are our three groups: "at the beginning of the programme", "midway through the programme" and "at the end of the programme").Īll 30 participants undergo treatment A and treatment B. The two treatments, known as "conditions", are a "massage programme" (treatment A) and "acupuncture programme" (treatment B). Therefore, 30 participants take part in the experiment. The researcher wants to find out whether one of two different treatments is more effective at reducing pain levels.
Imagine that a health researcher wants to help suffers of chronic back pain reduce their pain levels.
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