noinfmodel {dyad} | R Documentation |
Fit an autoregressive marriage model to husband and wife, with no influence.
noinfmodel(observations)
observations |
A data frame with two columns, one for the wife (person 1) and one for the husband (person 2) scores for each unit of time |
This function fits a model of marriage where input is a series of discrete observations of the wife (W) and the husband (H). The same model can apply to single-sex couples, in which case the wife should be interpreted as partner 1 and the husband as partner 2.
The model is as follows:
W(t+1) = a0 + a1*W(t)
H(t+1) = b0 + b1*H(t)
noinfmodel
returns a list consisting of the results (the
parameters fit by the model) for the wife
(person 1) and the husband (person 2). Each set of results is an object of class
noinfmodel
. Although variable names (e.g., a0
and a1) are the same for each object, their values correspond to the
model fit to the husband or wife (and are generally different for each
spouse). Therefore, a0 and a1 for the
husband's results should be interpreted as b0 and b1 in the equation
for the husband above.
An object of class noinfmodel
contains the
following parameters.
a0 |
Initial state |
a1 |
Inertia |
ss |
Sum squared residuals |
loglik |
Log likelihood assuming equal variance of residuals across regimes |
nparams |
Number parameters, assuming unequal variance of residuals across regimes |
BIC |
Bayesian Information Criterion |
AIC |
Akaike's Information Criterion |
nt |
Number of observations |
score |
Vector of partner data (from 1 to nt-1) |
influence |
Vector of influence, calculated using a0 and a1 above |
Tara Madhyastha and Ellen Hamaker
For a general description of the marriage model and influence functions, see Gottman, J. M., Murray, J. D., Swanson, C., Tyson, R., & Swanson, K. R. (2003). The Mathematics of Marriage: Dynamic Nonlinear Models. The MIT Press.
The method of parameter estimation used here is described in Hamaker, E., Zhang, Z., Van der Maas, H.L. Using threshold autoregressive models to study dyadic interactions. Psychometrika, in press.
linmodel
, ojivemodel
, combimodel
, origmodel
,bilinmodel
require(dyad) data(couple) ## fit a model with no influence fit <- noinfmodel(couple)