NKnotsTest {DAMisc}  R Documentation 
Estimate hypothesis test of lower and higherorder nonlinear relationships against an assumed target relationship.
NKnotsTest(
form,
var,
data,
targetdf = 1,
degree = 3,
min.knots = 1,
max.knots = 10,
adjust = "none"
)
form 
A formula detailing the model for which smoothing is to be evaluated. 
var 
A character string identifying the variable for which smoothing is to be evaluated. 
data 
Data frame providing values of all variables in 
targetdf 
The assumed degrees of freedom against which the tests will be conducted. 
degree 
Degree of polynomial in Bspline basis functions. 
min.knots 
Minimum number of internal Bspline knots to be evaluated. 
max.knots 
Maximum number of internal Bspline knots to be evaluated. 
adjust 
Method by which pvalues will be adjusted (see

A matrix with the following columns:
F 
F statistics of test of candidate models against target model 
DF1 
Numerator DF from Ftest 
DF2 
Denominator DF from Ftest 
p(F) 
pvalue from the Ftest 
Clarke 
Test statistic from the Clarke test 
Pr(Better) 
The Clarke statistic divided by the number of observations 
p(Clarke) 
pvalue from the Clarke test. (T) means that the significant pvalue is in favor of the Target model and (C) means the significant pvalue is in favor of the candidate (alternative) model. 
Delta_AIC 
AIC(candidate model)  AIC(target model) 
Delta_AICc 
AICc(candidate model)  AICc(target model) 
Delta_BIC 
BIC(candidate model)  BIC(target model) 
Dave Armstrong
data(Prestige, package="carData")
NKnotsTest(prestige ~ education + type, var="income", data=na.omit(Prestige), targetdf=3)