Pilot studies and experimental design

Specification: Pilot studies and the aims of piloting. Experimental design: repeated measures, independent groups, matched pairs.

Pilot studies

Pilot studies are smallscale prototypes of a study that are carried out in advance of the full research to find out if there are any problems with the following:

Carrying out a pilot study beforehand is a way to ensure time, effort and money are not wasted on a flawed methodology. It is important that a pilot study uses a sample that (although smaller) is representative of the target population that will be used in the main research.

Experimental design

The three main types of experimental design are:

Repeated measures

Repeated measures is a design where the same participants take part in each condition of the experiment. The data obtained from both conditions is then compared for each participant to see if there was a difference. 

Evaluation in repeated measures

There are strengths associated with using the repeated measures design. Since the same participants are taking part in all conditions of the experiment, fewer participants are required. This makes the design less costly and time consuming, as fewer participants need to be recruited. In addition, the use of the same participants across conditions reduces the possibility of participant variables such as individual differences playing a part in the different results obtained, meaning that the effect on the DV can be attributed to the IV with more confidence.

 

There are issues with adopting a repeated measures design in psychological research. As the same participants take part in both conditions of the experiment, order effects can occur. Participants who experience practice effects may perform better in the second conditions as they know what is expected of them. Participants who experience fatigue (boredom) may perform worse in the second condition, because they give up. To address this issue, researchers can use counterbalancing which offsets any order effects as half the participants take part in ‘Condition A’ followed by ‘Condition B’ while the other half complete the ‘Condition B’ followed by ‘Condition A’. Any order effects experienced by those who started in Condition A should be offset by those who started in Condition B. Furthermore, repeated measures experiments are also prone to demand characteristics as participants are more likely to guess the aim of the experiment when they take part in both conditions.

Independent groups

 An independent measures design uses of two separate groups of participants; one group in each condition of the experiment. Participants should be allocated to their group (condition) by random allocation, which ensures that each participant has an equal chance of being assigned to one group or the other. This is important to reduce investigator effects, resulting in a biased sample being placed into the two conditions, and the influence of individual differences whereby participant variables influence the measurements taken in the DV (dependent variable).

Evaluation of independent groups

A strength of using independent groups design is that it avoids order effects. As participants only take part in one condition of the experiment, they are less likely to become bored and give up reducing the impact of order effects. In addition, this research design also reduces demand characteristics, as participants are only taking part in one condition of the experiment. This means that they are less likely to guess the aim of the experiment and display demand characteristics, making the results higher in validity.

 

There are disadvantages of using an independent groups design. More participants are required as different people take part in the different conditions of the experiment. This makes the design more expensive and time consuming for the researcher who must recruit more individuals to take part. Additionally, participant variables may affect the results. For example, differences in age, sex or social background may affect the results by acting as an extraneous variable on the DV which means that psychologists cannot be certain that the IV caused the changes measured.

Matched pairs

Pairs of participants are matched from the sample, in terms of key variables such as age or IQ. After matching takes place, the participants are treated much like those in independent measures. One member of each pair is placed in the experimental group and the other member in the control group.

Evaluation of matched pairs

There are benefits of adopting a matched pairs research design in psychological research. Because the researcher pairs up the participants so that each condition has people with similar abilities and characteristics, this reduces participant variables. In addition, order effects (such as practice or fatigue) are less of an issue compared to a repeated measures design as the participants only take part in one condition of the experiment and therefore they are less likely to become bored and give up.

 

There are issues involved with creating a matched pairs research design. More participants are required, as different participants take part in the different conditions of the experiment, making the design more expensive and time consuming for the researcher. Furthermore, it is very difficult, if not impossible, trying to find close or exactly matched pairs. This means that individual differences may still play a role in the measurement of the DV reducing the certainty that the IV affected the change.

Summary of experimental design

POssible exam questions

Explain why Dr Lees might want to conduct a pilot study before the main observation is carried out. (2 marks)

Revision materials