plotprofile
Description
returns
an array of lines
= plotprofile(___)Line
objects for the lines in the plot.
Examples
Plot Means for One-Way MANOVA
Load the fisheriris
data set.
load fisheriris
The column vector species
contains iris flowers of three different species: setosa, versicolor, and virginica. The matrix meas
contains four types of measurements for the flower: the length and width of sepals and petals in centimeters.
Perform a one-way MANOVA with species
as the factor and the measurements in meas
as the response variables.
maov = manova(species,meas,FactorNames="species",ResponseNames=["SepalLength" "SepalWidth"... "PetalLength" "PetalWidth"])
maov = 1-way manova SepalLength,SepalWidth,PetalLength,PetalWidth ~ 1 + species Source DF TestStatistic Value F DFNumerator DFDenominator pValue _______ ___ _____________ ______ ______ ___________ _____________ __________ species 2 pillai 1.1919 53.466 8 290 9.7422e-53 Error 147 Total 149 Properties, Methods
maov
is a manova
object that contains the results of the one-way MANOVA. The small p-value for species
indicates that the flower species has a statistically significant effect on at least one of the flower measurements.
Create a profile plot of the mean measurements for each flower species.
plotprofile(maov) legend
The profile plot shows that the means are the most spread out for the petal length measurement, and that setosa has smaller measurements, on average, than the other two flower species.
Plot Means for Two-Way MANOVA
Load the carsmall
data set.
load carsmall
The variable Model_Year
contains data for the year a car was manufactured, and the variable Cylinders
contains data for the number of engine cylinders in the car. The Acceleration
and Displacement
variables contain data for car acceleration and displacement.
Use the table
function to create a table from the data in Model_Year
, Cylinders
, Acceleration
, and Displacement
.
tbl = table(Model_Year,Cylinders,Acceleration,Displacement,VariableNames=["Year" "Cylinders" "Acceleration" "Displacement"]);
Perform a two-way MANOVA using the table variables Year
and Cylinders
as factors, and the Acceleration
and Displacement
variables as response variables.
maov = manova(tbl,"Acceleration,Displacement ~ Cylinders + Year")
maov = 2-way manova Acceleration,Displacement ~ 1 + Year + Cylinders Source DF TestStatistic Value F DFNumerator DFDenominator pValue _________ __ _____________ ________ ______ ___________ _____________ __________ Year 2 pillai 0.084893 2.1056 4 190 0.081708 Cylinders 2 pillai 0.94174 42.27 4 190 2.5049e-25 Error 95 Total 99 Properties, Methods
maov
is a manova
object that contains the results of the two-way MANOVA. The table output shows that the p-value for the MANOVA model term Year
is too large to conclude that Year
has a statistically significant effect on the mean response vector. However, the small p-value for Cylinders
indicates that enough evidence exists to conclude that Cylinders
has a statistically significant effect on the mean response vector.
Create a profile plot of the means for Acceleration
and Displacement
grouped by the combinations of values for Year
and Cylinders
. Use the axes
function to create axes that plot lines in magenta, green, and black.
lineColors = [1 0 1; 0 1 0; 0 0 0]; ax = axes(ColorOrder=lineColors); plotprofile(ax,maov,["Year" "Cylinders"]) legend
The profile plot shows that the means for Acceleration
are similar. However, the color coding shows that the means for Displacement
are clustered by their corresponding values in Cylinders
. The top cluster, shown in black, corresponds to cars with eight-cylinder engines. The middle cluster, shown in green, corresponds to cars with six-cylinder engines. The bottom cluster, shown in magenta, corresponds to cars with four-cylinder engines. This result supports the conclusion that Cylinders
has a statistically significant effect on the mean response vector, but Year
does not.
Input Arguments
maov
— MANOVA results
manova
object
MANOVA results, specified as a manova
object.
The properties of maov
contain the factor values and response data
used by plotprofile
to create the profile plot.
factors
— Factors used to group response data
string vector | cell array of character vectors
Factors used to group the response data, specified as a string vector or a cell
array of character vectors. The plotprofile
function groups the
response data by the combinations of values for the factors in
factors
. The factors
argument must be one or
more categorical factor names in maov.FactorNames
.
Example: ["Factor1","Factor2"]
Data Types: string
| cell
ax
— Target axes
Axes
object
Target axes, specified as an Axes
object. If you do not specify the
axes, then plotprofile
uses the current axes (gca
).
Output Arguments
lines
— Profile plot lines
array of Line
objects
Profile plot lines, returned as an array of Line
object handles.
You can modify the properties of the Line
objects to customize the
profile plot. For a complete list of Line
properties, see Line Properties.
Version History
Introduced in R2023b
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