Last Update: February 21, 2022
Linearity in Parameters: Ramsey RESET Test in R can be done using lmtest
package resettest
function for evaluating whether linear regression fitted values non-linear combinations explain dependent variable. Main parameters within resettest
function are formula
with y ~ x
original model description, power
with augmented model added independent variables powers, type
with original model fitted values, independent variables or independent variables first principal component to be included as augmented model added independent variables and data
with data.frame
object including original model variables.
As example, we can do Ramsey RESET test on multiple linear regression of house price explained by its lot size and number of bedrooms using data included within AER
package HousePrices
object [1].
First, we load packages AER
for data and lmtest
for Ramsey RESET test [2].
In [1]:
library(AER)
library(lmtest)
Second, we create HousePrices
data object from AER
package using data
function and print first six rows and three columns of data using head
function to view data.frame
structure.
In [2]:
data(HousePrices)
head(HousePrices[, 1:3])
Out [2]:
price lotsize bedrooms
1 42000 5850 3
2 38500 4000 2
3 49500 3060 3
4 60500 6650 3
5 61000 6360 2
6 66000 4160 3
Third, as example again, we do Ramsey RESET test using resettest
function. Within resettest
function, parameters formula = price ~ lotsize + bedrooms
fits original model where house price is explained by its lot size and number of bedrooms, power = 2
adds squared independent variable to augmented model and type = "fitted"
adds original model fitted values as augmented model independent variable. Notice that resettest
function parameters power = 2
and type = "fitted"
were only included as educational examples which can be modified according to your needs.
In [3]:
resettest(formula = price ~ lotsize + bedrooms, data = HousePrices, power = 2, type = "fitted")
Out [3]:
RESET test
data: price ~ lotsize + bedrooms
RESET = 10.635, df1 = 1, df2 = 542, p-value = 0.00118
Courses
My online courses are hosted at Teachable website.
For more details on this concept, you can view my Linear Regression in R Course.
References
[1] Data Description: Sales prices of houses sold in the city of Windsor, Canada, during July, August and September, 1987.
Original Source: Anglin, P., and Gencay, R. (1996). Semiparametric Estimation of a Hedonic Price Function. Journal of Applied Econometrics, 11, 633–648.
[2] AER R Package: Christian Kleiber and Achim Zeileis. (2008). Applied Econometrics with R. Springer-Verlag, New York.
lmtest R Package: Achim Zeileis and Torsten Hothorn. (2002). Diagnostic Checking in Regression Relationships. R News, 2 (3): 7-10