R/ssm_analysis.R
ssm_score.Rd
Calculate the SSM parameters for each row of a data frame and add the results as additional columns. This can be useful when the SSM is being used for the description or visualization of individual data points rather than for statistical inference on groups of data points.
ssm_score(.data, scales, angles, ...)
.data | Required. A data frame containing at least circumplex scales. |
---|---|
scales | Required. The variable names or column numbers for the
variables in |
angles | Required. A numeric vector containing the angular displacement
of each circumplex scale included in |
... | Optional. Additional parameters to pass to
|
A data frame containing .data
plus six additional columns
containing the SSM parameters (calculated rowwise).
Other ssm functions:
ssm_analyze()
,
ssm_append()
,
ssm_parameters()
,
ssm_plot()
,
ssm_table()
Other analysis functions:
ssm_analyze()
,
ssm_parameters()
#> PA BC DE FG HI JK LM NO Elev Xval Yval #> 1 -1.09 -1.04 -0.97 0.61 1.41 2.49 1.78 0.27 0.4325 1.2514177 -1.3091258 #> 2 1.13 -1.04 -0.97 -0.79 -0.56 0.79 1.78 1.52 0.2325 1.4193555 0.5073528 #> 3 0.91 -0.65 -0.80 -0.96 -0.23 -0.34 1.24 0.27 -0.0700 0.7822361 0.4476346 #> 4 0.47 -0.45 -0.29 0.26 1.57 1.36 1.60 0.48 0.6250 0.8313567 -0.5560749 #> 5 0.45 0.32 0.43 0.96 1.25 1.41 1.49 0.85 0.8950 0.4382412 -0.4121320 #> Ampl Disp Fit #> 1 1.8110374 313.70892 0.9706769 #> 2 1.5073079 19.66958 0.9172710 #> 3 0.9012602 29.78035 0.7137698 #> 4 1.0001866 326.22237 0.8784837 #> 5 0.6015880 316.75861 0.9674101