The alignment method improves measurement fairness in developmental science by adjusting item thresholds to match the distribution of responses across groups. It is particularly useful for multi-category items and can be interpreted using R packages. Ignoring differences in thresholds can lead to inaccurate group mean differences, especially for intersectional groups. Item-level partial non-invariance results should be interpreted in the context of group-level differences and substantive theorizing about measurement fairness is encouraged.

Format: Paperback / softback
Length: 75 pages
Publication date: 06 July 2023
Publisher: Cambridge University Press

This Element delves into the realm of measurement fairness in developmental science, shedding light on its significance and potential applications. It elucidates the alignment method, elucidating its core principles and rationale. Through an accessible and engaging narrative, it demonstrates the method's application to multi-category items, offering practical insights and sample code. Moreover, it showcases an R package designed to facilitate the interpretation of such items across multiple thresholds. The Element underscores the implications of disregarding differences in thresholds between categories when treating items as continuous, emphasizing the potential impact on group mean differences, particularly in the context of intersectional groups defined by factors such as assigned sex and race/ethnicity. It further illustrates the interpretation of item-level partial non-invariance results and their implications for group-level differences, encouraging substantive theorizing regarding measurement fairness. By exploring these topics, this Element serves as a valuable resource for researchers and practitioners seeking to enhance the fairness and accuracy of developmental science assessments.

Measurement Fairness in Developmental Science: The Alignment Method

In the field of developmental science, measurement fairness is a critical concern as it ensures that assessments are equitable and unbiased. The alignment method is a powerful tool that can advance this goal by addressing the issue of item bias and ensuring that items measure the same construct across different groups.

The alignment method involves several steps. First, it involves identifying the construct of interest, which is the underlying concept or trait that researchers want to measure. Next, a set of items is developed that measure this construct in a way that is consistent across different groups. This ensures that the items are valid and reliable for all groups.

One of the key advantages of the alignment method is that it can be applied to multi-category items. These items are typically used to measure complex constructs such as personality, attitudes, or behaviors. By aligning the items across different categories, researchers can ensure that the items are measuring the same construct for all groups.

To illustrate the application of the alignment method, consider the example of a personality test that includes items such as "I am a good listener," "I am outgoing," and "I am creative." These items are intended to measure the construct of extroversion. However, it is possible that these items may be biased against certain groups, such as individuals who identify as introverted or who have a different cultural background.

To address this issue, the alignment method can be used. First, the items can be reviewed to identify any potential biases. For example, the items may be reworded to make them more inclusive or culturally sensitive. Additionally, the item difficulty can be adjusted to ensure that all groups have an equal chance of answering the items correctly.

Once the items have been aligned, they can be administered to different groups. The results can then be compared to determine if there are any group mean differences. If there are, this can indicate that the items are biased against certain groups.

To address this issue, the alignment method can be used again. The items can be re-evaluated to identify any additional biases or difficulties. Additionally, the thresholds for categorizing individuals into different groups can be adjusted to ensure that they are based on meaningful differences rather than arbitrary categorizations.

In conclusion, the alignment method is a powerful tool that can advance measurement fairness in developmental science. By identifying and addressing item bias, researchers can ensure that assessments are equitable and unbiased for all groups. The application of the alignment method to multi-category items is particularly important, as it allows researchers to measure complex constructs in a way that is consistent across different groups. Through substantive theorizing regarding measurement fairness, researchers can continue to enhance the fairness and accuracy of developmental science assessments.

ISBN-13: 9781009357746