probit {sampleSelection} | R Documentation |
This function calculates probit binary choice model
probit(formula, subset, na.action, start = NULL, data = sys.frame(sys.parent()), x=FALSE, y = FALSE, model = FALSE, method="ML", ... )
formula |
a symbolic description of the model to be fit, in the
form response ~ explanatory variables
(see also details). |
subset |
an optional vector specifying a subset of observations to be used in the fitting process. |
na.action |
a function which indicates what should happen when the data contain 'NA's. The default is set by the 'na.action' setting of 'options', and is 'na.fail' if that is unset. The 'factory-fresh' default is 'na.omit'. Another possible value is 'NULL', no action. Value 'na.exclude' can be useful. |
start |
inital value of parameters. |
data |
an optional data frame containing the variables in the
model. If not found in data, the
variables are taken from environment(formula), typically the
environment from which probit is called. |
x, y, model |
logicals. If TRUE the corresponding components of the fit (the model matrix, the response, the model frame) are returned. |
method |
the method to use; for fitting, currently only method = "ML" (Maximum Likelihood) is supported; method = "model.frame" returns the model frame (the same as with model = TRUE, see below). |
... |
further arguments for maxLik . |
The model is estimated using Maximum Likelihood method.
The dependent variable must have exactly
two levels (e.g. '0' and '1', 'FALSE' and 'TRUE', or 'no' and 'yes').
probit
always takes the first level as '0' and
the second level as '1' – no matter the actual value.
However, by default levels are sorted in increasing order and thus,
the second level is generally, e.g., '1' (after '0'),
'TRUE' (after 'FALSE'), or 'yes' (after 'no').
An object of class "probit". It is a list with following components:
LRT |
Likelihood ration test. The full model is tested against
H0: the parameters have no effect on the result. This is a list
with components
|
nParam |
Number of parameters of the model including constant |
nObs |
Number of the observations |
N1 |
Number of observations with non-zero (true) response |
N0 |
Number of observations with zero (false) response |
df |
Number of free parameters |
x |
if requested, the model matrix used. |
y |
if requested, the model response used. The response is represented internally as 0/1 integer vector. |
model |
the model frame, only if model = TRUE or
method = "model.frame" . |
Other components are inherited from maxLik
.
Ott Toomet otoomet@ut.ee
maxLik
for ready-packaged likelihood maximisation
routines and methods, glm
for generalised linear models,
including probit, binomial
.
## A simple MC trial: note probit assumes normal errors x <- runif(100) e <- 0.5*rnorm(100) y <- x + e summary(probit((y > 0) ~ x)) ## female labour force participation probability data(Mroz87) Mroz87$kids <- Mroz87$kids5 > 0 | Mroz87$kids618 > 0 Mroz87$age30.39 <- Mroz87$age < 40 Mroz87$age50.60 <- Mroz87$age >= 50 summary(probit(lfp ~ kids + age30.39 + age50.60 + educ + hushrs + huseduc + huswage + mtr + motheduc, data=Mroz87))