# Profile.resid: Residuals In multicon: Multivariate Constructs

## Description

Computes the residuals for each observation (row) where items pairs are the corresponding columns in x.set and y.set.

## Usage

 `1` ```Profile.resid(x.set, y.set, nomiss = 0.8) ```

## Arguments

 `x.set` A data.frame or matrix, with the same dimensions as y.set, of which each row is a predictor of the corresponding row in y.set. `y.set` A data.frame or matrix, with the same dimensions as x.set, of which each row is to be predicted by the correpsonding row in x.set. `nomiss` A numeric between .00 and 1.00 specifying the proportion of x-y pairs required to be complete before NA is returned instead of the regression coefficients. The default of .80 means that if more than 20 percent of the x-y pairs are incomplete an NA will be returned.

## Details

The residuals from predicting the values in each row of y.set from the values in the corresponding row of y.set are returned. If fewer than 'nomiss' of the x-y pairs of observations for a given row are valid (complete) then NA will be returned for all of that row's residuals.

## Value

Returns a data.frame of the same size as x.set containing the residual values of y.set after being predicted by x.set.

## Author(s)

Ryne A. Sherman

`Profile.reg` `lin.coef`
 ``` 1 2 3 4 5 6 7 8 9 10``` ```data(acq1) data(caq) #Lets get the regression coeficients for predicting aquaintance #California Adult Q-Set (CAQ) personality ratings from #self-report CAQ ratings Profile.reg(caq,acq1) #We can look at the residuals from those regressions res.acq <- Profile.resid(acq1, caq) head(res.acq) ```