Description Usage Arguments Details Value Examples

View source: R/estimating_funct_expr.R

Function to compute `logL1`

and `logL2`

under the GLM and AFT setting
for the analysis of a normally-distributed and of a censored time-to-event
primary outcome. `logL1`

and `logL2`

are functions which underlie
the estimating functions of CIEE for the derivation of point estimates and
standard error estimates. `est_funct_expr`

computes their
expression, which is then further used in the functions `deriv_obj`

,
`ciee`

and `ciee_loop`

.

1 | ```
est_funct_expr(setting = "GLM")
``` |

`setting` |
String with value |

Under the GLM setting for the analysis of a normally-distributed primary
outcome `Y`

, the goal is to obtain estimates for the pararameters
*α0, α1, α2, α3, σ1^2, α4, αXY, σ2^2*
under the model

*Y = α0 + α1*K + α2*X + α3*L + ε1, ε1 ~ N(0,σ1^2)*

*Y* = Y - mean(Y) - α1*(K-mean(K))*

*Y* = α0 + αXY*X + ε2, ε2 ~ N(0,σ2^2).*

`logL1`

underlies the estimating functions for the derivation of the
first 5 parameters
*α0, α1, α2, α3, σ1^2*
and
`logL2`

underlies the estimating functions for the derivation of the
last 3 parameters
*α4, αXY, σ2^2*.

Under the AFT setting for the analysis of a censored time-to-event primary
outcome `Y`

, the goal is to obtain estimates of the parameters
*α0, α1, α2, α3, σ1, α4, αXY, σ2^2*.
Here, `logL1`

similarly underlies the estimating functions
for the derivation of the first 5 parameters and `logL2`

underlies the
estimating functions for the derivation of the last 3 parameters.

`logL1`

, `logL2`

equal the log-likelihood functions (`logL2`

given that *α1* is known). For more details and the underlying model,
see the vignette.

Returns a list containing the expression of the functions `logL1`

and `logL2`

.

1 2 | ```
est_funct_expr(setting = "GLM")
est_funct_expr(setting = "AFT")
``` |

CIEE documentation built on May 2, 2019, 6:39 a.m.

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