calcallgroups: Calculates the social status determinations of multiple...

In SSrat: Two-Dimensional Sociometric Status Determination with Rating Scales

Description

Calculates the social status determinations from a SSrat compliant dataframe, as described in readratdatafixed.
The dataframe may contain multiple groups. This function can only be used when the rating scale is equal for all groups.
Basically, this function calls the calcgroup function as often as there are groups in the SSrat compliant dataframe.
The resulting dataframe with social sttaus determinations can be analyzed with standard tools for statistical analyis, such as linear regression (lm). Other data, such as background variables can be added to the dataframe.

Usage

calcallgroups(dataframe, alpha = c(0.1, 0.05, 0.01), NBcriteria = F)

Arguments

dataframe	The input dataframe with the rating data. This dataframe should have columns schoolid, groupid, respid, and for n raters n columns named "r01", "r02" .. "r<n>", with a maximum of r99.
alpha	The significance levels to be applied to the probability distributions of the four total scores that have been derived from the ratings. By choosing an appropriate alpha, the user can fine tune the criterion for the status determination. A list of various alphas can be supplied. Default is the list (.10, .05, .01).
NBcriteria	A boolean. When TRUE, the classification criteria of Newcomb & Bukowski (1983) will be applied, in stead of the SSrat criteria. These criteria are applicable to three-point rating scales. When this option is selected for longer scales, the scale midpoint is recoded to 2, all scores larger than the midscore are recoded to 3 and all scores lower than the midscore are recoded to 1. When another recoding scheme is preferred, the input ratings themselves should be recoded (use recode from package car).

Details

See function calcgroup for more details.

Value

dataframe	dataframe with the most relevant output of SSrat, calculated for each rated respondent
dataframe$schoolid	school id as entered in the input dataframe
dataframe$groupid	group id as entered in the input dataframe
dataframe$respid	respondent id as entered in the input data frame
dataframe$nrAss	number of assessors who have given a valid rating
dataframe$tr.S	total rating Sympathy
dataframe$tr.A	total rating Antipathy
dataframe$tr.P	total rating Preference
dataframe$tr.I	total rating Impact
dataframe$SS.xx	Social Determination as attributed by SSrat, applying alpha = .xx. Defaults to SS.10, SS.05 and SS.01

Note

Use calcgroup for generating more detailed information on social status determination.

Author(s)

Hans Landsheer

References

Coie, J. D., Dodge, K. A., & Coppotelli, H.(1982). Dimensions and types of social status: A cross-age perspective. Developmental Psychology, 18, 557-570.
Coie, J.D., & Dodge, K.A. (1983). Continuities and changes in children's social status: A five-year longitudinal study. Merril-Palmer Quarterly, 29, 261-282.
Newcomb, A. F., & Bukowski, W. M. (1983). Social impact and social preference as determinants of children's peer group status. Developmental Psychology, 19, 856-867.
Maassen, G. H. and Landsheer, J. A. (1998). SSRAT: The processing of rating scales for the determination of two-dimensional sociometric status. Behavior Research Methods Instruments & Computers, 30(4), 674-679.

See Also

readratdatafixed calcgroup

Examples

data(example5.rat)
calcgroup (school=1, group=23, data=example5.rat, scalelength="3")$dataframe
calcallgroups(example5.rat)

#readmultiple groups
data(example6.rat)
calcallgroups(example6.rat)

data(example7.rat)
calcallgroups(example7.rat) # Wrong!
calcgroup (school=1, group=1, dataframe=example7.rat, scalelength="7")$dataframe
calcgroup (school=1, group=3, dataframe=example7.rat, scalelength="7")$dataframe
calcgroup (school=2, group=1, dataframe=example7.rat, scalelength="7")$dataframe

#use names
data(example1a.rat)
calcallgroups(example1a.rat)

SSrat documentation built on May 2, 2019, 11:26 a.m.