faoutlier (version 0.7.6)

obs.resid: Model predicted residual outliers

Description

Compute model predicted residuals for each variable using regression estimated factor scores.

Usage

obs.resid(data, model, ...)
# S3 method for obs.resid
print(x, restype = "obs", ...)
# S3 method for obs.resid
plot(
  x,
  y = NULL,
  main = "Observed Residuals",
  type = c("p", "h"),
  restype = "obs",
  ...
)

Arguments

data

matrix or data.frame

model

if a single numeric number declares number of factors to extract in exploratory factor analysis. If class(model) is a sem (semmod), or lavaan (character), then a confirmatory approach is performed instead

...

additional parameters to be passed

x

an object of class obs.resid

restype

type of residual used, either 'obs' for observation value (inner product), 'res' or 'std_res' for unstandardized and standardized for each variable, respectively

y

a NULL value ignored by the plotting function

main

the main title of the plot

type

type of plot to use, default displays points and lines

References

Chalmers, R. P. & Flora, D. B. (2015). faoutlier: An R Package for Detecting Influential Cases in Exploratory and Confirmatory Factor Analysis. Applied Psychological Measurement, 39, 573-574. 10.1177/0146621615597894

Flora, D. B., LaBrish, C. & Chalmers, R. P. (2012). Old and new ideas for data screening and assumption testing for exploratory and confirmatory factor analysis. Frontiers in Psychology, 3, 1-21. 10.3389/fpsyg.2012.00055

See Also

gCD, LD, robustMD

Examples

# NOT RUN {
# }
# NOT RUN {
data(holzinger)
data(holzinger.outlier)

#Exploratory
nfact <- 3
(ORresult <- obs.resid(holzinger, nfact))
(ORresult.outlier <- obs.resid(holzinger.outlier, nfact))
plot(ORresult)
plot(ORresult.outlier)

#-------------------------------------------------------------------
#Confirmatory with sem
model <- sem::specifyModel()
   F1 -> Remndrs,    lam11
	  F1 -> SntComp,    lam21
	  F1 -> WrdMean,    lam31
	  F2 -> MissNum,    lam41
	  F2 -> MxdArit,    lam52
	  F2 -> OddWrds,    lam62
	  F3 -> Boots,      lam73
  F3 -> Gloves,     lam83
	  F3 -> Hatchts,    lam93
	  F1 <-> F1,   NA,     1
	  F2 <-> F2,   NA,     1
	  F3 <-> F3,   NA,     1

(ORresult <- obs.resid(holzinger, model))
(ORresult.outlier <- obs.resid(holzinger.outlier, model))
plot(ORresult)
plot(ORresult.outlier)

#-------------------------------------------------------------------
#Confirmatory with lavaan
model <- 'F1 =~  Remndrs + SntComp + WrdMean
F2 =~ MissNum + MxdArit + OddWrds
F3 =~ Boots + Gloves + Hatchts'

(obs.resid2 <- obs.resid(holzinger, model, orthogonal=TRUE))
(obs.resid2.outlier <- obs.resid(holzinger.outlier, model, orthogonal=TRUE))
plot(obs.resid2)
plot(obs.resid2.outlier)

# }