What Is Survivorship Bias? | Definition & Examples

Survivorship bias occurs when researchers focus on individuals, groups, or cases that have passed some sort of selection process while ignoring those who did not. Survivorship bias can lead researchers to form incorrect conclusions due to only studying a subset of the population. Survivorship bias is a type of selection bias.

Survivorship bias example
A hospital is conducting research on trauma patients admitted to the ER, seeking to find out which procedures work best. However, researchers can only begin their studies if a patient is stable enough to give consent. Because the trial excludes everyone who didn’t survive their injuries or is too sick to consent, survivorship bias may occur.

In addition to being a common form of research bias, survivorship bias can also lead to poor decision-making in other areas, such as finance, medicine, and business.

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What Is Selection Bias? | Definition & Examples

Selection bias refers to situations where research bias is introduced due to factors related to the study’s participants. Selection bias can be introduced via the methods used to select the population of interest, the sampling methods, or the recruitment of participants. It is also known as the selection effect.

Example: Selection bias
Health studies that recruit participants directly from clinics miss all the cases who don’t attend those clinics or seek care during the study.

Due to this, the sample and the target population may differ in significant ways, limiting your ability to generalize your findings.

Selection bias may threaten the validity of your research, as the study population is not representative of the target population.

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What Is the Pygmalion Effect? | Definition & Examples

The Pygmalion effect refers to situations where high expectations lead to improved performance and low expectations lead to worsened performance. Although the Pygmalion effect was originally observed in the classroom, it also has been applied to in the fields of management, business, and sports psychology.

Example: Pygmalion effect
You want to research the influence of two storytelling methods on the vocabulary size improvement of children. To test this, the children are either given 20 minutes of storytelling from their teacher or 20 minutes of computerized storytelling.

You strongly believe the human aspect is needed to aid in the vocabulary development of children. You encourage the children in that group to pay attention and be excited, whereas you don’t show this behavior to the computer group.

The children in the first group are now paying more attention and feeling better about themselves than children in the other group, potentially leading to a Pygmalion effect.

The Pygmalion effect is also known as the Rosenthal effect, after the researcher who first observed the phenomenon.

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What Is the Hawthorne Effect? | Definition & Examples

The Hawthorne effect refers to people’s tendency to behave differently when they become aware that they are being observed. As a result, what is observed may not represent “normal” behavior, threatening the internal and external validity of your research.

The Hawthorne effect is also known as the observer effect and is closely linked with observer bias.

Example: Hawthorne effect
You are researching the smoking rates among bank employees as part of a smoking cessation program. You collect your data by watching the employees during their work breaks.

If employees are aware that you are observing them, this can affect your study’s results. For example, you may record higher or lower smoking rates than are genuinely representative of the population under study.

Like other types of research bias, the Hawthorne effect often occurs in observational and experimental study designs in fields like medicine, organizational psychology, and education.

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What Is Confirmation Bias? | Definition & Examples

Confirmation bias is the tendency to seek out and prefer information that supports our preexisting beliefs. As a result, we tend to ignore any information that contradicts those beliefs.

Confirmation bias is often unintentional but can still lead to poor decision-making in (psychology) research and in legal or real-life contexts.

Example: Confirmation bias
During presidential elections, people tend to seek information that paints the candidate they support in a positive light, while dismissing any information that paints them in a negative light.

This type of research bias is more likely to occur while processing information related to emotionally charged topics, values, or deeply held beliefs.

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Inclusion and Exclusion Criteria | Examples & Definition

Inclusion and exclusion criteria determine which members of the target population can or can’t participate in a research study. Collectively, they’re known as eligibility criteria, and establishing them is critical when seeking study participants for clinical trials.

This allows researchers to study the needs of a relatively homogeneous group (e.g., people with liver disease) with precision. Examples of common inclusion and exclusion criteria are:

  • Demographic characteristics: Age, gender identity, ethnicity
  • Study-specific variables: Type and stage of disease, previous treatment history, presence of chronic conditions, ability to attend follow-up study appointments, technological requirements (e.g., internet access)
  • Control variables: Fitness level, tobacco use, medications used

Failure to properly define inclusion and exclusion criteria can undermine your confidence that causal relationships exist between treatment and control groups, affecting the internal validity of your study and the generalizability (external validity) of your findings.

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What Is Predictive Validity? | Examples & Definition

Predictive validity refers to the ability of a test or other measurement to predict a future outcome. Here, an outcome can be a behavior, performance, or even disease that occurs at some point in the future.

Example: Predictive validity
A pre-employment test has predictive validity when it can accurately identify the applicants who will perform well after a given amount of time, such as one year on the job.

Predictive validity is a subtype of criterion validity. It is often used in education, psychology, and employee selection.

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What Is Concurrent Validity? | Definition & Examples

Concurrent validity shows you the extent of the agreement between two measures or assessments taken at the same time. It compares a new assessment with one that has already been tested and proven to be valid.

Concurrent validity is a subtype of criterion validity. It is called “concurrent” because the scores of the new test and the criterion variables are obtained at the same time.

Example: Concurrent validity
You want to assess the concurrent validity of a new survey measuring employee commitment. To do so, you can either:

  1. Ask the same sample of employees to fill in both an existing (validated) survey and your new survey. Then compare the results.
  2. Ask a sample of employees to fill in your new survey. Then, compare their responses to the results of a common measure of employee performance, such as a performance review.

If the results of the two measurement procedures are similar, you can conclude that they are measuring the same thing (i.e., employee commitment). This demonstrates concurrent validity.

Establishing concurrent validity is particularly important when a new measure is created that claims to be better in some way than existing measures: more objective, faster, cheaper, etc.

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What Is Ecological Validity? | Definition & Examples

Ecological validity measures how generalizable experimental findings are to the real world, such as situations or settings typical of everyday life. It is a subtype of external validity.

If a test has high ecological validity, it can be generalized to other real-life situations, while tests with low ecological validity cannot.

Example: Ecological validity
You are researching whether airline passengers pay attention to in-flight safety videos. You are interested in whether or not they can recall specific information from them. You recruit a sample of 100 people and send them a safety video, asking them to watch it on their own time. Afterwards, you send them a questionnaire to find out what they can recall from the video.

Using this approach, your findings would have low ecological validity. The experience of watching the video at home is vastly different from watching it on a plane.

To achieve high ecological validity, the best approach would be to conduct the experiment on an actual flight.

Ecological validity is often applied in experimental studies of human behavior and cognition, such as in psychology and related fields.

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What Is Criterion Validity? | Definition & Examples

Criterion validity (or criterion-related validity) evaluates how accurately a test measures the outcome it was designed to measure. An outcome can be a disease, behavior, or performance. Concurrent validity measures tests and criterion variables in the present, while predictive validity measures those in the future.

To establish criterion validity, you need to compare your test results to criterion variables. Criterion variables are often referred to as a “gold standard” measurement. They comprise other tests that are widely accepted as valid measures of a construct.

Example: Criterion validity
A researcher wants to know whether a college entrance exam is able to predict future academic performance. First-semester GPA can serve as the criterion variable, as it is an accepted measure of academic performance.

The researcher can then compare the college entry exam scores of 100 students to their GPA after one semester in college. If the scores of the two tests are close, then the college entry exam has criterion validity.

When your test agrees with the criterion variable, it has high criterion validity. However, criterion variables can be difficult to find.

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