Sometimes basic descriptive measures for constructs and elements, e.g. mean, standard deviation, are neeeded. To prompt descriptive statistics for the constructs and elements of a grid use the function statsConstructs and statsElements. The following measures are returned:

• item name
• item number
• number of valid cases
• mean
• standard deviation
• trimmed mean (with trim defaulting to .1)
• median (standard or interpolated)
• mad: median absolute deviation (from the median)
• minimum
• maximum
• skew
• kurtosis
• standard error

# R-Code

The following examples are identical for statsElements. Just replace statsConstructs by statsElements in order to analyze elements.

d <- statsConstructs(fbb2003)
d

####################################
Desriptive statistics for constructs
####################################

vars n mean   sd median trimmed  mad min max range  skew kurtosis   se
(1) clever - not bright        1 8 3.75 2.31    4.0    3.75 2.97   1   7     6  0.02    -1.84 0.82
(2) disorganiz - organized     2 8 4.00 1.77    4.5    4.00 2.22   2   6     4 -0.13    -1.96 0.63
(3) listens - doesn't he       3 8 3.50 2.14    3.0    3.50 2.22   1   7     6  0.35    -1.40 0.76
(4) no clear v - clear view    4 8 4.38 1.60    4.0    4.38 1.48   3   7     4  0.38    -1.68 0.56
(5) understand - no underst    5 8 3.50 1.85    2.5    3.50 0.74   2   6     4  0.41    -1.90 0.65
(6) ambitious - no ambitio     6 8 4.50 1.51    4.5    4.50 2.22   3   7     4  0.33    -1.58 0.53
(7) respected - not respec     7 8 3.25 1.75    3.0    3.25 1.48   1   6     5  0.23    -1.67 0.62
(8) distant - warm             8 8 4.12 1.96    4.0    4.12 1.48   1   7     6 -0.05    -1.46 0.69
(9) rather agg - not aggres    9 8 3.62 1.92    3.0    3.62 2.22   1   7     6  0.36    -1.25 0.68

The returned object is a dataframe, so you may access them as usual. E.g. to retrieve the means of the constructs, type

d\$mean
[1] 3.750 4.000 3.500 4.375 3.500 4.500 3.250 4.125 3.625
statsConstructs(fbb2003, trim = 10)

####################################
Desriptive statistics for constructs
####################################

vars n mean   sd median trimmed  mad min max range  skew kurtosis   se
(1) cleve - not b    1 8 3.75 2.31    4.0    3.75 2.97   1   7     6  0.02    -1.84 0.82
(2) disor - organ    2 8 4.00 1.77    4.5    4.00 2.22   2   6     4 -0.13    -1.96 0.63
(3) liste - doesn    3 8 3.50 2.14    3.0    3.50 2.22   1   7     6  0.35    -1.40 0.76
(4) no cl - clear    4 8 4.38 1.60    4.0    4.38 1.48   3   7     4  0.38    -1.68 0.56
(5) under - no un    5 8 3.50 1.85    2.5    3.50 0.74   2   6     4  0.41    -1.90 0.65
(6) ambit - no am    6 8 4.50 1.51    4.5    4.50 2.22   3   7     4  0.33    -1.58 0.53
(7) respe - not r    7 8 3.25 1.75    3.0    3.25 1.48   1   6     5  0.23    -1.67 0.62
(8) dista - warm     8 8 4.12 1.96    4.0    4.12 1.48   1   7     6 -0.05    -1.46 0.69
(9) rathe - not a    9 8 3.62 1.92    3.0    3.62 2.22   1   7     6  0.36    -1.25 0.68
statsConstructs(fbb2003, index=F)

####################################
Desriptive statistics for constructs
####################################

vars n mean   sd median trimmed  mad min max range  skew kurtosis   se
clever - not bright        1 8 3.75 2.31    4.0    3.75 2.97   1   7     6  0.02    -1.84 0.82
disorganiz - organized     2 8 4.00 1.77    4.5    4.00 2.22   2   6     4 -0.13    -1.96 0.63
listens - doesn't he       3 8 3.50 2.14    3.0    3.50 2.22   1   7     6  0.35    -1.40 0.76
no clear v - clear view    4 8 4.38 1.60    4.0    4.38 1.48   3   7     4  0.38    -1.68 0.56
understand - no underst    5 8 3.50 1.85    2.5    3.50 0.74   2   6     4  0.41    -1.90 0.65
ambitious - no ambitio     6 8 4.50 1.51    4.5    4.50 2.22   3   7     4  0.33    -1.58 0.53
respected - not respec     7 8 3.25 1.75    3.0    3.25 1.48   1   6     5  0.23    -1.67 0.62
distant - warm             8 8 4.12 1.96    4.0    4.12 1.48   1   7     6 -0.05    -1.46 0.69
rather agg - not aggres    9 8 3.62 1.92    3.0    3.62 2.22   1   7     6  0.36    -1.25 0.68