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Reliability (statistics)

Assessing Reliability

❶A test can be split in half in several ways, e.

What is Reliability?

Inter-Rater or Inter-Observer Reliability
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Split-half method

The scale is reliable because it consistently reports the same weight every day, but it is not valid because it adds 5lbs to your true weight. It is not a valid measure of your weight. If a measure of art appreciation is created all of the items should be related to the different components and types of art.

If the questions are regarding historical time periods, with no reference to any artistic movement, stakeholders may not be motivated to give their best effort or invest in this measure because they do not believe it is a true assessment of art appreciation. Construct Validity is used to ensure that the measure is actually measure what it is intended to measure i.

The experts can examine the items and decide what that specific item is intended to measure. Students can be involved in this process to obtain their feedback.

The questions are written with complicated wording and phrasing. It is important that the measure is actually assessing the intended construct, rather than an extraneous factor. Criterion-Related Validity is used to predict future or current performance - it correlates test results with another criterion of interest.

If a physics program designed a measure to assess cumulative student learning throughout the major. The new measure could be correlated with a standardized measure of ability in this discipline, such as an ETS field test or the GRE subject test. At the other extreme, any experiment that uses human judgment is always going to come under question. Human judgment can vary wildly between observers , and the same individual may rate things differently depending upon time of day and current mood.

This means that such experiments are more difficult to repeat and are inherently less reliable. Reliability is a necessary ingredient for determining the overall validity of a scientific experiment and enhancing the strength of the results.

Debate between social and pure scientists, concerning reliability, is robust and ongoing. Validity encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. For example, there must have been randomization of the sample groups and appropriate care and diligence shown in the allocation of controls.

Internal validity dictates how an experimental design is structured and encompasses all of the steps of the scientific research method. Even if your results are great, sloppy and inconsistent design will compromise your integrity in the eyes of the scientific community. Internal validity and reliability are at the core of any experimental design. External validity is the process of examining the results and questioning whether there are any other possible causal relationships. Control groups and randomization will lessen external validity problems but no method can be completely successful.

This is why the statistical proofs of a hypothesis called significant , not absolute truth. Any scientific research design only puts forward a possible cause for the studied effect. There is always the chance that another unknown factor contributed to the results and findings. This extraneous causal relationship may become more apparent, as techniques are refined and honed. If you have constructed your experiment to contain validity and reliability then the scientific community is more likely to accept your findings.

The goal of reliability theory is to estimate errors in measurement and to suggest ways of improving tests so that errors are minimized. The central assumption of reliability theory is that measurement errors are essentially random. This does not mean that errors arise from random processes. For any individual, an error in measurement is not a completely random event. However, across a large number of individuals, the causes of measurement error are assumed to be so varied that measure errors act as random variables.

If errors have the essential characteristics of random variables, then it is reasonable to assume that errors are equally likely to be positive or negative, and that they are not correlated with true scores or with errors on other tests. It is assumed that: Reliability theory shows that the variance of obtained scores is simply the sum of the variance of true scores plus the variance of errors of measurement.

In its general form, the reliability coefficient is defined as the ratio of true score variance to the total variance of test scores. Or, equivalently, one minus the ratio of the variation of the error score and the variation of the observed score:.

Unfortunately, there is no way to directly observe or calculate the true score , so a variety of methods are used to estimate the reliability of a test. Some examples of the methods to estimate reliability include test-retest reliability , internal consistency reliability, and parallel-test reliability. Each method comes at the problem of figuring out the source of error in the test somewhat differently. It was well-known to classical test theorists that measurement precision is not uniform across the scale of measurement.

Tests tend to distinguish better for test-takers with moderate trait levels and worse among high- and low-scoring test-takers.

Item response theory extends the concept of reliability from a single index to a function called the information function.

The IRT information function is the inverse of the conditional observed score standard error at any given test score. Four practical strategies have been developed that provide workable methods of estimating test reliability.

The correlation between scores on the first test and the scores on the retest is used to estimate the reliability of the test using the Pearson product-moment correlation coefficient: The key to this method is the development of alternate test forms that are equivalent in terms of content, response processes and statistical characteristics.

For example, alternate forms exist for several tests of general intelligence, and these tests are generally seen equivalent.

If both forms of the test were administered to a number of people, differences between scores on form A and form B may be due to errors in measurement only.

The correlation between scores on the two alternate forms is used to estimate the reliability of the test. This method provides a partial solution to many of the problems inherent in the test-retest reliability method. For example, since the two forms of the test are different, carryover effect is less of a problem. Reactivity effects are also partially controlled; although taking the first test may change responses to the second test. However, it is reasonable to assume that the effect will not be as strong with alternate forms of the test as with two administrations of the same test.

This method treats the two halves of a measure as alternate forms. It provides a simple solution to the problem that the parallel-forms method faces: The correlation between these two split halves is used in estimating the reliability of the test.

Test-Retest Reliability

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Reliability refers to whether or not you get the same answer by using an instrument to measure something more than once. In simple terms, research reliability is the degree to which research method produces stable and consistent results. A specific measure is considered to be reliable if its.

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Reliability has to do with the quality of measurement. In its everyday sense, reliability is the "consistency" or "repeatability" of your measures. Before we can define reliability precisely we have to .

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Internal validity dictates how an experimental design is structured and encompasses all of the steps of the scientific research method. Even if your results are great, sloppy and inconsistent design will compromise your integrity in the eyes of the scientific community. Internal validity and reliability are at the core of any experimental design. Research Methods › Reliability. What is Reliability? Saul McLeod, published The term reliability in psychological research refers to the consistency of a research study or measuring test. For example, if a person weighs themselves during the course of a day they would expect to see a similar reading. Scales which measured weight Author: Saul Mcleod.

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You are here: AllPsych > Research Methods > Chapter Test Validity and Reliability Test Validity and Reliability Whenever a test or other measuring device is used as part of the data collection process, the validity and reliability of that test is important. Inter-method reliability assesses the degree to which test scores are consistent when there is a variation in the methods or instruments used. This allows inter-rater reliability to be ruled out. This allows inter-rater reliability to be ruled out.