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# response

Class: LinearMixedModel

Response vector of the linear mixed-effects model

## Syntax

y = response(lme)

## Description

y = response(lme) returns the response vector y used to fit the linear mixed-effects model lme.

## Input Arguments

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### lme — Linear mixed-effects modelLinearMixedModel object

Linear mixed-effects model, returned as a LinearMixedModel object.

For properties and methods of this object, see LinearMixedModel.

## Output Arguments

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### y — Response valuesn-by-1 vector

Response values, specified as an n-by-1 vector, where n is the number of observations.

Data Types: single | double

## Examples

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### Plot Response versus Fitted Values

Navigate to a folder containing sample data.

```cd(matlabroot)
cd('help/toolbox/stats/examples')```

`load weight`

weight contains data from a longitudinal study, where 20 subjects are randomly assigned to 4 exercise programs, and their weight loss is recorded over two-week time periods. This is simulated data.

Store the data in a table. Define Subject and Program as categorical variables.

```tbl = table(InitialWeight,Program,Subject,Week,y);
tbl.Subject = nominal(tbl.Subject);
tbl.Program = nominal(tbl.Program);
```

Fit a linear mixed-effects model where the initial weight, type of program, week, and the interaction between the week and type of program are the fixed effects. The intercept and week vary by subject.

`lme = fitlme(tbl,'y ~ InitialWeight + Program*Week + (Week|Subject)');`

Compute the fitted values and the response.

```F = fitted(lme);
y = response(lme);```

Plot the response versus the fitted values.

```plot(F,y,'bs')
xlabel('Fitted Values')
ylabel('Response')```