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, ...)

Arguments

.data

Required. A data frame containing at least circumplex scales.

scales

Required. The variable names or column numbers for the variables in .data that contain circumplex scales to be analyzed.

angles

Required. A numeric vector containing the angular displacement of each circumplex scale included in scales (in degrees).

...

Optional. Additional parameters to pass to ssm_parameters(), such as prefix and suffix.

Value

A data frame containing .data plus six additional columns containing the SSM parameters (calculated rowwise).

See also

Other ssm functions: ssm_analyze(), ssm_append(), ssm_parameters(), ssm_plot(), ssm_table()

Other analysis functions: ssm_analyze(), ssm_parameters()

Examples

data("aw2009") ssm_score(aw2009, scales = PA:NO, angles = octants())
#> 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