How can I do a necessity experiment?

How can I do an (large N) observational study with NCA?

How can I do a (small N) case study with NCA?

How can I do an archival study with NCA?

How can I do a meta-analysis/systematic review with NCA

How can I do a necessity experiment?

In an experiment the condition (X) is manipulated and the effect on the outcome (Y) is observed. In the regular sufficiency experiment cases without  (or with a low level of) the outcome are selected and the condition is added (or increased) to observe whether the outcome appears (“Gain of function experiment”) by looking at the average effect compared to a control group where the manipulation was not done. In the necessity experiment cases with (or with a high level of) the outcome are selected and the condition is eliminated (or reduced) to observe whether the outcome disappears (“Loss of function experiment”) by looking at the maximum effect compared to a control group where the manipulation was not done.

How can I do an (large N) observational study with NCA?

In a (large N) observational study the condition (X) and the outcome (Y) are observed in real-life context without manipulation of the condition. There is no difference between a sufficiency observational research design, and necessity observational research design. Only the data analysis differs. For causal interpretation a theoretical explanation is essential (necessity hypothesis).

How can I do a (small N) case study with NCA?

In a (small N) case study the condition (X) and the outcome (Y) are observed in real-life context. The regular sufficiency case study explores conditions (X) that may produce the outcome (Y). The necessity case study identifies the common (hence necessary) conditions (X), in one or more cases with the outcome (Y). For exploration (theory building) there is no difference between a sufficiency case study research design, and necessity case study research design. Only the data analysis differs. However, whereas the case study can not be used for testing sufficiency theory, it can be used for testing necessity theory. Even one case (and a deterministic view on necessity) can reject a necessity theory, when the assumed necessary condition is not present in a case where the outcome is present.  

How can I do an archival study with NCA?

In an archival study, an existing data set (usually from an observational study) is used to perform a theory building or testing study. In the regular archival study the data are (re)analysed for building or testing sufficiency theory. In the necessity archival study the data are analysed using NCA for building or testing necessity theory. Using NCA with archival data is particularly useful since the data are usually only analysed with a probabilistic sufficiency causal perspective on XY relationships, whereas NCA can add the necessity perspective.   

How can I do a meta-analysis/systematic review with NCA

In a meta-analysis/systematic reviews findings from several studies are combined to obtain an overall picture of the evidence of the relationship between X and Y. In the regular sufficiency meta-analysis/systematic review sufficiency effect sizes or correlation coefficients are compared. In a necessity meta-analysis/systematic review necessity effect sizes are compared. However, existing sufficiency studies do not report necessity effect sizes or ceiling lines. When raw data or scatter plots are reported in sufficiency studies, necessity effect sizes and ceiling lines can be calculated or approximated.