How do you prevent attrition?

To avoid attrition, applying some of these measures can help you reduce participant dropout by making it easy and appealing for participants to stay.

Provide compensation (e.g., cash or gift cards) for attending every session
Minimize the number of follow-ups as much as possible
Make all follow-ups brief, flexible, and convenient for participants
Send participants routine reminders to schedule follow-ups
Recruit more participants than you need for your sample (oversample)
Maintain detailed contact information so you can get in touch with participants even if they move

Frequently asked questions: Research bias

Why are placebos used in research?: Placebos are used in medical research for new medication or therapies, called clinical trials. In these trials some people are given a placebo, while others are given the new medication being tested.

The purpose is to determine how effective the new medication is: if it benefits people beyond a predefined threshold as compared to the placebo, it’s considered effective.
What causes the placebo effect?: Although there is no definite answer to what causes the placebo effect, researchers propose a number of explanations such as the power of suggestion, doctor-patient interaction, classical conditioning, etc.
What are common types of selection bias?: Common types of selection bias are:

Sampling or ascertainment bias

Attrition bias

Volunteer or self-selection bias

Survivorship bias

Non-response bias

Undercoverage bias
Why is bias in research a problem?: Bias affects the validity and reliability of your findings, leading to false conclusions and a misinterpretation of the truth. This can have serious implications in areas like medical research where new forms of treatment are being evaluated.
What is the difference between response and nonresponse bias?: Response bias is a general term used to describe a number of different conditions or factors that cue respondents to provide inaccurate or false answers during surveys or interviews. These factors range from the interviewer’s perceived social position or appearance to the the phrasing of questions in surveys.

Nonresponse bias occurs when the people who complete a survey are different from those who did not, in ways that are relevant to the research topic. Nonresponse can happen because people are either not willing or not able to participate.
What is the difference between observer bias and actor–observer bias?: Observer bias occurs when the researcher’s assumptions, views, or preconceptions influence what they see and record in a study, while actor–observer bias refers to situations where respondents attribute internal factors (e.g., bad character) to justify other’s behavior and external factors (difficult circumstances) to justify the same behavior in themselves.
Why is bias in research a problem?: Research bias affects the validity and reliability of your research findings, leading to false conclusions and a misinterpretation of the truth. This can have serious implications in areas like medical research where, for example, a new form of treatment may be evaluated.
What is the difference between stratified and cluster sampling?: Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous, so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous, as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population.
What is a sampling method?: When your population is large in size, geographically dispersed, or difficult to contact, it’s necessary to use a sampling method.

This allows you to gather information from a smaller part of the population (i.e., the sample) and make accurate statements by using statistical analysis. A few sampling methods include simple random sampling, convenience sampling, and snowball sampling.
What is the definition of social desirability bias?: Social desirability bias is a type of response bias that occurs when survey respondents provide answers according to society’s expectations, rather than their own beliefs or experiences.

It is especially likely to occur in self-report questionnaires, as well as in any type of behavioral research, particularly if the participants know they’re being observed. This research bias can distort your results, leading to over-reporting of socially desirable behaviors or attitudes and under-reporting of socially undesirable behaviors or attitudes.
What is the observer-expectancy effect?: The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.

Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics.

The observer-expectancy effect is often used synonymously with the Pygmalion or Rosenthal effect.
How can I minimize observer bias in my research?: You can use several tactics to minimize observer bias.

Use masking (blinding) to hide the purpose of your study from all observers.

Triangulate your data with different data collection methods or sources.

Use multiple observers and ensure interrater reliability.

Train your observers to make sure data is consistently recorded between them.

Standardize your observation procedures to make sure they are structured and clear.
Can I avoid observer bias?: It’s impossible to completely avoid observer bias in studies where data collection is done or recorded manually, but you can take steps to reduce this type of bias in your research.
What is observer bias?: Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. This type of research bias is also called detection bias or ascertainment bias.
How do you overcome attrition bias?: If you have a small amount of attrition bias, you can use some statistical methods to try to make up for it.

Multiple imputation involves using simulations to replace the missing data with likely values. Alternatively, you can use sample weighting to make up for the uneven balance of participants in your sample.
How does attrition affect external validity?: Attrition bias can skew your sample so that your final sample differs significantly from your original sample. Your sample is biased because some groups from your population are underrepresented.

With a biased final sample, you may not be able to generalize your findings to the original population that you sampled from, so your external validity is compromised.
How does attrition threaten internal validity?: Attrition bias is a threat to internal validity. In experiments, differential rates of attrition between treatment and control groups can skew results.

This bias can affect the relationship between your independent and dependent variables. It can make variables appear to be correlated when they are not, or vice versa.
Why is attrition bias a problem?: Some attrition is normal and to be expected in research. However, the type of attrition is important because systematic bias can distort your findings. Attrition bias can lead to inaccurate results because it affects internal and/or external validity.
What is attrition bias?: Attrition bias is the selective dropout of some participants who systematically differ from those who remain in the study.

Some groups of participants may leave because of bad experiences, unwanted side effects, or inadequate incentives for participation, among other reasons. Attrition is also called subject mortality, but it doesn’t always refer to participants dying!
What’s the difference between demand characteristics and social desirability bias?: Demand characteristics are aspects of experiments that may give away the research purpose to participants. Social desirability bias is when participants automatically try to respond in ways that make them seem likeable in a study, even if it means misrepresenting how they truly feel.

Participants may use demand characteristics to infer social norms or experimenter expectancies and act in socially desirable ways, so you should try to control for demand characteristics wherever possible.
How do I prevent demand characteristics?: You can control demand characteristics by taking a few precautions in your research design and materials.

Use these measures:

Deception: Hide the purpose of the study from participants

Between-groups design: Give each participant only one independent variable treatment

Double-blind design: Conceal the assignment of groups from participants and yourself

Implicit measures: Use indirect or hidden measurements for your variables
Why do demand characteristics matter in research?: Demand characteristics are a type of extraneous variable that can affect the outcomes of the study. They can invalidate studies by providing an alternative explanation for the results.

These cues may nudge participants to consciously or unconsciously change their responses, and they pose a threat to both internal and external validity. You can’t be sure that your independent variable manipulation worked, or that your findings can be applied to other people or settings.
What are demand characteristics?: In research, demand characteristics are cues that might indicate the aim of a study to participants. These cues can lead to participants changing their behaviors or responses based on what they think the research is about.

Demand characteristics are common problems in psychology experiments and other social science studies because they can cause a bias in your research findings.
What is sampling bias?: Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.

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