Age Equivalent is the individual's ability; skill, knowledge, or measurement expressed as the age at which most individuals reach the same level (age norm). The Age Norm is the average score of a particular test completed by children of a given chronological age.
For example, the mental age norm of a 6-year old female is determined by collecting a sample of 6-year old female children’s mental abilities, then calculating that average cognitive function as the age norm. This average mental function is the age norm for that group. The cognitive function equivalent of the 6-year-old female will then be compared against this age norm.
Age Equivalents are not only used in intelligence measurement, but also physical development such as physical growth (i.e., height and weight, verbal quantity and quality) and motor skills. There are age equivalents, timetables of development, for both prenatal and throughout childhood.
Some tests which use age equivalents include: WIAT, Oral and Written Language Scales-Written Expression (OWLS WE), Peabody gross motor scale, Mullen Scales of Early Learning for the Assessment of Young Children with Autism Spectrum Disorders, and some early intervention tests. Some tests will use age norms as an additional evaluation tool with standard scores.
Age equivalents only report relative standing of different students on the same test and are more intuitively understandable. They give a frame of reference for growth and can provide problem-warning signs.
Since there is a relationship between maturation and learning, it suggests a timetable. But because individuals are different, they cannot be expected to be in the same place at the same time. Even though two children are the same mental age, they may not both be ready for the same school tasks, such as reading.
Because of comparisons to norms, failing to master developmental tasks as expected may cause unfavorable social judgments and a limited foundation for later tasks. Care should be taken to avoid a negative (self) judgment resulting in feelings of inadequacy.
Age equivalents are ordinal data, which means there are not equal units between scores. The development curves are higher in younger children and plateau with older children and adults. Because of this, there are larger differences between scores of younger as compared to older children. Unless the practitioner understands the difference in the amount of variance, it may cause difficulty with the interpretation; as such, should not be used alone to make decisions.
Standardized tests usually use normative scores, so there is a measurement within an age group. Standard scores provide a more accurate view of an examinee’s ability because they are based not only on the mean at a given age level but also on the distribution of scores within the age group. Age equivalents are measured in groups between ages. Age norms are calculated from group scores, not individuals within the group.
Analysis of variance from the mean cannot be calculated with age equivalents. Age norms assume scores are evenly distributed, but there is no way to know how the scores are in actuality clustered. If scores cluster around the top or bottom of the scale it means that change can only be detected in the other direction. This introduces a bias called “ceiling” or “floor” effects. In a ceiling effect, the majority of scores is at or near the maximum possible for the test and is limited by a lack of variability. This presents statistical problems. The test can’t measure traits above its ceiling. This violates statistical assumptions and limits reliability results.
Relevance to Childhood Development
Age equivalents are used to make decisions about intellectual development, academic achievement, and the discrepancy between them to help identify Learning Disabilities (LD). It also measures comparisons of intellectual ability. IQ is a measure of intelligence calculated by mental age divided by actual age. Even the fact that IQ can change illustrates the problem with analyzing mental age. To minimize this occurrence, it is statistically calculated as a distribution on the bell curve.
Growth and Development
One of the more universally accepted theories is that child development is sequential in nature; that there is often a hierarchy of skills creating milestones or stages. Since all humans go through the same steps, comparisons should be able to be made. Stages are monitored from babyhood on up, observing these steps. The approximate ages at which steps occur are charted on developmental scales. Generally, development is measured in the following areas: fine motor, gross motor, cognitive, self-help, social emotional, and expressive and receptive language. Age equivalents are compared to age norms to determine if development is occurring as expected.