Nonnormative influences are influences which don’t influence every member of a set in the same way. The term normative refers to something that affects everyone in a culture at the same time, so nonnormative implies it affects everyone differently (or not at all).
In psychology, they’re the things that change an individual’s life but not the lives of other people in the same way. They can be very important in a person’s life, but they aren’t universal and don’t have patterns or predictable sequences that we can easily see. They don’t happen at a set time; instead, they are unexpected in the lives of those they affect. Although they can happen at any life stage, nonnormative life events are thought to be particularly significant for middle-aged and older adults (Baltes et al., 1980, cited in Woolf, 1998).
More generally, nonnormative influences are random, unpredictable influences that affect one member (or a random sample of members) of a larger data set.
Examples of Nonnormative Influences
The death of a friend in a road accident, an unexpected major disease diagnosis, or winning the lottery are all examples of nonnormative influences on an individual.
A particular event may be a nonnormative influence event from one perspective and not from another. For instance, from the perspective of a sociologist studying personal finance and spending, an unexpected divorce may consist of a nonnormative influence on a person’s life. However, from a family sociologist’s viewpoint, the divorce might not have been characterized as either inexplicable, unpredictable, or random: it had its roots in certain social relations and/or actions long before.
Categorization something as a non-normative influence has more to do with being unexplainable and unpredictable in a given paradigm or model than whether it indeed is truly a random occurrence in the grand scheme of life.
The Place of Nonnormative Influences in Statistical Analysis
Since they can’t be modeled by mathematical equations, nonnormative influences are often relegated to error terms when conducting statistical analysis. They don’t lend themselves well to large scale data analysis. However, because of their potentially enormous influence on an individual, they can’t be ignored and form an important part of the big picture in any psychological research project.
Featherman, D. et, al (2014). Life-Span Development and Behavior, Volume 11. Psychology Press.
Woolf, L. (1998). Theoretical Perspectives Relevant to Developmental Psychology. Retrieved December 18, 2017 from http://faculty.webster.edu/woolflm/designs.html
If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.Comments? Need to post a correction? Please post on our Facebook page.