What is Predictive Validity and how it should be used in workplace?

One of the assessments that companies now use in the recruitment process is cognitive ability tests. One of the most important components of these tests is the G factor, which measures an individual’s mental capacity. Under the G factor, three things are measured: unified cognitive capacity, relationships with specific abilities, and Predictive Validity. 

We will understand predictive Validity and assess its importance in today’s world. We will also examine how the advent of artificial intelligence is modernizing predictive analytics. So, what is Predictive Validity, and how is it measured?

What is Predictive Validity?

Predictive Validity is the extent or degree to which any test can accurately measure future outcomes or behaviors. Cognitive ability tests are excellent at achieving predictive Validity, which is why they have been adopted by a large portion of the recruitment industry.

In recent times, artificial intelligence has given rise to a new field called predictive analytics, which helps transform data to predict future outcomes. 

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Components of Predictive Validity 

Test or Predictor Measure

A test measure, also called predictor measures, is a set of tools, instruments, or methods used in assessments to determine or forecast future preferences. These measures allow recruiters to assess how a candidate might react to a certain situation in the future.

The types of tests used under the predictor measures:

• Cognitive Test: Cognitive Ability Tests, also called Aptitude Tests, measure individuals’ intellectual capacity across various spectrums. 
• Personality Assessments: Personality assessments are questionnaires prepared in an interview that gauge a candidate’s social skills, soft skills, etc.
• Skills Test: This test evaluates specific skills related to the job to assess how the candidate executes those skills in real-life situations.
• Structured Interviews: Under this methodology, each candidate is asked the same standardized interview questions. This helps eliminate bias in the recruitment process.

Also Read: How to create a fair cognitive ability test?

Criterion Variable

The Criterion Variable is the actual results or outcomes of the predator measures test used to analyze their skills.The criterion variable’s accuracy depends on how well the predictor tests correlate with real-life scenarios. One of the most common areas where the criterion variable is used is during recruitment.

The things that can used to assess the effectiveness of the criterion variable are:

• Job Performance Ratings: This includes evaluations from peers, seniors, and managers at previous organizations, which give an idea of the candidate’s strengths and weaknesses.
• Objective performance metrics: This means quantifying the candidates’ work using several metrics to assess their work. For example, for a marketing role, metrics like sales figures, error rates, and customer satisfaction scores should be used.
• Training success: To analyze whether the performance of candidates improved or regressed after going through training programs on which their organizations spend money.

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Time Interval

Time Interval in the predictive validity realm is defined as the gap between when the predictor is measured and when the criterion validity results come through. Based on different scenarios, a typical time interval can range from months to years, as is demonstrated by the table below.

Context	Typical Time Interval
Employment (e.g., job performance)	3–12 months after hiring
Education (e.g., GPA or graduation)	1–4 years
Training programs	End of training or several weeks/months after
Clinical outcomes	6 months to a year post-intervention

The reason why time interval is important in predictive validity is:

• Demonstrates actual prediction: The time gap helps a recruiter assess the degree of accuracy of their prediction or estimate of a candidate. The results also allow them to discover the shortcomings of the process, helping them improve upon them.
• Simulates real-world situations: In the workplace, months of work allow ample opportunity to see how they perform in a real-life scenario.
• Separate cause and effect: This helps avoid reverse causation between the predictor measure and criterion variable.

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Statistical Correlation

Under statistical correlation, the strength of the relationship between the predictor measure and criterion validity is measured. So, if a person scores high on the predictor measures, does this lead to better outcomes in the criterion validity after a few months?

One of the commonly used statistical correlations is called the Pearson correlation coefficient. In this test, candidates are given a score from +1 to -1.

r Value	Strength
0.00–0.19	Very weak
0.20–0.39	Weak
0.40–0.59	Moderate
0.60–0.79	Strong
0.80–1.00	Very strong

The formula that is used to measure statistical correlation is as follow:

R =∑(X−Xˉ)2∑(Y−Yˉ)2

      ∑(X−Xˉ)(Y−Yˉ)​

X in this scenario is the predictor measured and Y is criterion values.

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Sample Representativeness

Sample Representativeness means assessing whether the group used in sampling is similar to the target group to which the criterion variable will be applied. In the absence of sample representativeness, predictor measures might end up overestimating or underestimating, which might increase the chances of bad hires. So, a test might look efficient and give good scores, but it might fail by the time criterion variable results arrive.

The characteristics that might be kept in mind while sample representing:

• Demographics: Under this, metrics such as age, gender, ethnicity, religion, and educational qualifications must be considered.
• Role Type: This includes things such as role, duties, responsibilities, and the performance expected from the employees.
• Experience: The tasks and duties that should be evaluated must be factored into the survey if companies are filling a junior-level role.
• Geographic Location: If the sample is used to assess certain regional or cultural differences, it should be taken from outside the geographical location.

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Control of Confounding Variables

Confounding variables are factors that may be unaccounted for, hidden, uncontrolled, or even unintended and may influence the predictor measures and criterion variable. These variables make it hard for anyone to understand whether the predictor measures are accurate or are influenced by hidden factors.

So, how can we control these confounding variables?

• Statistical Controls: These involve multiple regression, ANCOVA, or partial correlation to check the influence of any hidden factors.
• Design Controls: This involves using design controls so as to minimize the impact of confounding variables on these tests.
• Clear Operational Definitions: Before the test, both the predictor and criterion and their reliability should be clearly defined.
• Blind Ratings: This involves appointing two different persons to rate the predator (test scores) and the criterion(results), decreasing the chances of bias in the process.

The world of recruitment has gone through a massive change in recent years especially with the rise in Artificial Intelligence. One result for this is the advent of what we now know as Interview as a Service (IaaS) companies which has taken recruitment to the next level. 

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BarRaise is one of the finest IaaS services that provides end-to-end hiring solutions for companies. Our tool acts as a virtual assistant during each part of the recruitment, be it pre-interview, interview and post-interview.

Our state-of-the-art tool gives companies the perfect interview tool that makes quality hiring easy. With BarRaiser users get our AI Interview Copilot that helps the recruiters in conducting a smooth, flawless interview.

Our product analyzes the interview and gives helpful suggestions to the interviewers on what questions to ask and to maintain the speed of the interview. In addition, it also analyzes the recruiter to ensure the interview process is not discriminatory in any way. Our tool can raise an alert if the hiring manager is asking for information which may be pertinent to the interview or the job description. This ensures perfect checks and balances in the system. We also use structured interviews format to ensure that there are less chances of bias seeping into the recruitment process.

So, what are you waiting for? Use BarRaiser and watch your hiring game go from good to best.