Specify a priori expectations for a nomological network

nomo_hypotheses() converts named theoretical predictions into a machine-readable object that can later be evaluated by nomo_network(). Relations use A -> B for directed structural paths and A <-> B for associations/covariances.

Usage

nomo_hypotheses(...)

Arguments

...

Named nomo_expectations created by positive(), negative(), or negligible(). Names must specify relations using -> or <->.

Value

A nomo_hypotheses object whose hypotheses field is one row per hypothesis: its relation, prediction, theoretical region, scale, and origin. n is the number of hypotheses.

Details

The function records theory; it does not inspect data, fit a model, or infer predictions from statistical significance.

References

Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281-302. doi:10.1037/h0040957

Lakens, D., Scheel, A. M., & Isager, P. M. (2018). Equivalence testing for psychological research: A tutorial. Advances in Methods and Practices in Psychological Science, 1(2), 259-269. doi:10.1177/2515245918770963

Nosek, B. A., Ebersole, C. R., DeHaven, A. C., & Mellor, D. T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences, 115(11), 2600-2606. doi:10.1073/pnas.1708274114

See also

nomo_network() to evaluate the hypotheses.

Examples

h <- nomo_hypotheses(
  "GSE -> Spirituality" = positive(),
  "GSE -> Religiosity" = negligible(within = c(-.10, .10)),
  "Religiosity <-> Spirituality" = positive(min = .20)
)
h
#> <nomo_hypotheses> Theory-specified relations
#> 3 theory-specified relations
#> 
#> Every relation is on the standardized scale.
#>   ID  Relation                      Prediction  Region       Origin
#>   H1  GSE -> Spirituality           positive    (0, +Inf)    a priori
#>   H2  GSE -> Religiosity            negligible  [-0.1, 0.1]  a priori
#>   H3  Religiosity <-> Spirituality  positive    [0.2, +Inf)  a priori