CRAN upload v0.6

Version 0.6

Changes

• Prettier output for equalMeans function.
• Fixed a bug when variances where constrained to be positive in a model with group comparisons and no mean structures: In this case, only the variances of the first group were constrained. Now it's fixed: both groups are constrained.
• Added new data sets: clinical, clinical.wide, two.groups, two.groups.wide
• When running a two-group analysis, plots automatically show both groups side-by-side
• Fixed a bug where the ordering of labels in the meanstructure-plot was wrong

Version 0.5

Changes

• Removed setZero option from fSRM. Replaced it with the option noNegVar. If this is TRUE, all variances are constrained to be > 0. (Older publications contrained negative variances to be exactly zero. This, however, leads to a distortion of the df). By default, this option is turned off, as negative variances should be recognized as an indicator of model misspecification.
• Added rolesEqual option to fSRM: Do roles matter at all? Compare a model with free roles (m1 <- fSRM(..., means=TRUE, rolesEqual = FALSE)) and a model with equal roles (m2 <- fSRM(..., means=TRUE, rolesEqual=TRUE)) using anova(m1$fit, m2$fit). This is a model with no mean difference, the actor variances equal, partner variances equal, relationship variances equal, and the respective reciprocities equal (Thanks to a suggestion of David Kenny).
• If missing values are present, by default missing = "fiml" is set, and a warning is issued that this is only valid if the data are missing completely at random (MCAR) or missing at random (MAR). Use missing = "listwise" to exclude families with missing values.
• Moved all dependencies to Imports so that no manual installation of packages is necessary for unexperienced users.
• By default, one-sided p values and CIs are printed for variances.
• Added plotting methods for fSRM objects: plot(x) gives a plot of the relative variances; plot(x, means=TRUE) gives a plot of the mean structure decomposition.
• Significance stars are printed in the output & nicer formatting of p values.