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Slot: interaction_with

The other terms this term is a product of -- what makes this column an interaction column. Populate it when the source names an interaction term in one model; leave it empty when the source describes a regression on a contrast.

The terms it may name are those of this model and of the stages it reaches through inputs_from, which is how a group stage crosses a cohort factor with a first-level condition: the product column is declared where it was fitted and names the lower stage's column directly.

A crossing of two factors is normally read off the cells, since a factor compared against itself carries a positive cell and a negative one. A continuous term has no levels and so cannot be crossed that way, which makes this slot the only record of a moderation such as age x group; the derived kind reads it before variation_level.

A product of terms that are all categorical and all crossed is legal but decides nothing, the crossed cells already saying what it says, and is flagged for review.

A product column declares no levels of its own; a signed cell on one with a continuous component may name a level of the factor, saying whose slope the sign describes. Such a column is not a covariate of a contrast whose cells name all of its components.

URI: neurostudy_ex:interaction_with

Applicable Classes

Name Description Modifies Slot
ModelTerm One term of the model: a column of the design matrix, or the equivalent predi... no

Properties

Type and Range

Property Value
Range ModelTerm
Domain Of ModelTerm
### Cardinality and Requirements
Property Value
Multivalued Yes

Slot Characteristics

Property Value
Owner ModelTerm

Identifier and Mapping Information

Schema Source

  • from schema: https://neurostuff.org/schemas/neuroimaging-study-extraction

Mappings

Mapping Type Mapped Value
self neurostudy_ex:interaction_with
native neurostudy_ex:interaction_with

LinkML Source

name: interaction_with
description: 'The other terms this term is a product of -- what makes this column
  an interaction column. Populate it when the source names an interaction term in
  one model; leave it empty when the source describes a regression on a contrast.

  The terms it may name are those of this model and of the stages it reaches through
  `inputs_from`, which is how a group stage crosses a cohort factor with a first-level
  condition: the product column is declared where it was fitted and names the lower
  stage''s column directly.

  A crossing of two factors is normally read off the cells, since a factor compared
  against itself carries a positive cell and a negative one. A continuous term has
  no levels and so cannot be crossed that way, which makes this slot the only record
  of a moderation such as `age x group`; the derived kind reads it before `variation_level`.

  A product of terms that are all categorical and all crossed is legal but decides
  nothing, the crossed cells already saying what it says, and is flagged for review.

  A product column declares no `levels` of its own; a signed cell on one with a continuous
  component may name a level of the factor, saying whose slope the sign describes.
  Such a column is not a covariate of a contrast whose cells name all of its components.'
from_schema: https://neurostuff.org/schemas/neuroimaging-study-extraction
rank: 1000
owner: ModelTerm
domain_of:
- ModelTerm
range: ModelTerm
multivalued: true
inlined: false