View source: R/logical_estimation.R
approx_and  R Documentation 
approx_and
approximates the linear model for the a conjunction
of m phenotypes as a function of a set of predictors.
approx_and(
means,
covs,
n,
predictors,
add_intercept = TRUE,
verbose = FALSE,
response_assumption = "binary",
...
)
means 
vector of predictor and response means with the last 
covs 
a matrix of the covariance of all model predictors and the
responses with the order of rows/columns corresponding to the order of

n 
sample size. 
predictors 
list of objects of class 
add_intercept 
logical. Should the linear model add an intercept term? 
verbose 
should output be printed to console? 
response_assumption 
character. Either 
... 
additional arguments 
an object of class "pcsslm"
.
An object of class "pcsslm"
is a list containing at least the
following components:
call 
the matched call 
terms 
the 
coefficients 
a 
sigma 
the square root of the estimated variance of the random error. 
df 
degrees of freedom, a 3vector 
fstatistic 
a 3vector with the value of the Fstatistic with its numerator and denominator degrees of freedom. 
r.squared 

adj.r.squared 
the above 
cov.unscaled 
a 
Sum Sq 
a 3vector with the model's Sum of Squares Regression (SSR), Sum of Squares Error (SSE), and Sum of Squares Total (SST). 
wolf_using_2021pcsstools
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