# lmtp 1.5.4

### New Features

### Bug Fixes

### General

- Added check that the number of Super Learner cross-validation folds isn't greater than the number of clusters (see issue \#105).
- `origami` has been removed as a dependency.
- Now requires `ife` version be greater than 0.1.2 (see issue \#180).
- Risk ratio and odds ratio in `lmtp_contrast` are now estimated on the log scale and then the estimate and confidence intervals are exponentiated (see issue \#180).

# lmtp 1.5.3

### New Features

### Bug Fixes

- Fixes bug where the `shifted` argument wouldn't work with multivariate exposure (see issue \#175).
- Fixes bug where `mtp = FALSE` wouldn't work with multivariate exposure. 

### General

# lmtp 1.5.2

### New Features

### Bug Fixes

### General

- The default for the `mtp` argument has been changed from `FALSE` to `TRUE` (see issue \#170).
- A warning message is now printed in `lmtp_contrast()` that p-values aren't adjusted for multiple comparisons (see issue \#172).
- A warning message is now printed in `lmtp_contrast()` if `ref` is a constant.

# lmtp 1.5.1

### New Features

### Bug Fixes

- Super learner prediction failing for some learners. Now using `onlySL = TRUE` in `predict.SuperLearner` (see issue \#162).

### General

- Making sure to only pass the necessary variables to `predict.SuperLearner` to suppress some warnings. 

# lmtp 1.5.0

### New Features

-   Added the ability to estimate the so-called "total effect" for survival outcome with competing risks (see issue \#143).
-   IPW and g-computation estimators are no-longer supported; they have been given deprecation errors. 
-   Added `lmtp_survival()` function for estimating the entire survival curve. Enforces monotonicity using isotonic regression (see issue \#140).

### Bug Fixes

-   Using fitted values from isotonic regression in `lmtp_survival()` instead of the original values (see issue \#149).

### General

-   Removed dependency on `schoolmath` which used a very slow function for testing if a vector was "decimalish".
-   Fixed "F used instead of FALSE" error in CRANs tests.

# lmtp 1.4.0

### New Features

-   Can now estimate the effects of simultaneous interventions on multiple variables. 
-   New pre-packaged shift function, `ipsi()` for estimating IPSI effects using the risk ratio.
-   `lmtp_control()` now replaces extra estimator arguments.

### Bug Fixes

-   Standard errors now incorporate survey weights (see issue \#134).
-   Bug fix when shift is NULL and data is a tibble (see issue \#137)

### General

-   The `intervention_type` argument has been fully deprecated.
-   Now attempting to detect intervention type errors (see issue \#98).

# lmtp 1.3.3

### New Features

### Bug Fixes

-   Fixed a bug where estimators return incorrect parameter estimates for a specific DGP (see issue \#130)

### General

# lmtp 1.3.2

### New Features

### Bug Fixes

-   Fixed bug in calculation of EIF where density ratios were not non-cumulative product ratios. Previous variance estimates starting with version 1.0 were incorrect. Point-estimates remain unaffected. 

### General

-   Updating citations

# lmtp 1.3.1

### New Features

-   Added parameter `.return_full_fits`. Allows the user to decide if full SuperLearner fit should be returned (issue \#119).
-   `intervention_type` argument replaced with `mtp`. 

### Bug Fixes

-   Added a check for `fits$id` being `NULL`. Fixes a backwards compatibility bug (issue \#117).
-   `data.table` version must be 1.13.0 or later. This was when the function `fcase` was released (issue \#122).

### General

-   Changed 'effect' to 'estimate' in 'Population mean effects' portion of output (issue \#120).

# lmtp 1.3.0

### New Features

### Bug Fixes

### General

-   Major internal refactor. Argument checking is now performed using *checkmate* package. 
-   `.SL_folds` argument split into `.learners_outcome_folds` and `.learners_trt_folds`.

# lmtp 1.1.0

### New Features

### Bug Fixes

-   Corrected standard errors when providing  `id` with `lmtp_contrast` (issue \#110).

### General

-   Removed the requirement that `folds` must be greater than 1 (issue \#112).

# lmtp 1.0.0

### New Features

-   New `shifted` parameter for directly passing shifted data instead of using a shift function (issue \#89).
-   New `intervention_type` parameter required for specifying if the intervention of interest is a static regime, a dynamic regime, or a modified treatment policy (issue \#94).
-   `return_all_ratios` removed as an argument. Returned density ratios are now non-cumulative product ratios.

### Bug Fixes

-   Density ratio trimming now occurs in the same spot for all estimators and is only performed on non-cumulative product ratios (issue #\93).
-   Fixed issue where `lmtp_tmle` and `lmtp_sdr` weren't using validation set density ratios.
-   No longer fails when `data` is a `data.table` (issue \#88).

### General

-   Removing extra column in `sim_point_surv` data set (issue \#91).
-   Paper citation updated with release in JASA (issue \#103).

# lmtp 0.9.1

### Bug Fixes

- Fixed a bug that caused failure when knitting the `getting-started.Rmd` vignette when using new version of the *future* package (issue \#100).

### General

- GitHub links added to DESCRIPTION (issue \# 99).

### Bug Fixes

-   Fixed a bug that caused failure when no variation existed in the outcome at a type point (issue \#92).
-   No longer fails when `data` is a `data.table` (issue \#88).

### General

-   Removing extra column in `sim_point_surv` data set (issue \#91).

# lmtp 0.9.0

### New Features

-   New `weights` parameter for observation sampling weights (issue \#78).

-   For time-to-event analysis, survival probability is now estimated instead of the cumulative incidence. This fixes a bug with IPW and survival problems.

-   Outcome type now accepts `"survival"` for explicit indication of a survival outcome (issue \#76). Because of this `lmtp_ipw()` now requires setting the outcome type.

-   New `.trimming` parameter for trimming extreme density ratios.

-   New `.SL_folds` parameter that controls the splits used for fitting the SuperLearner (issue \#84).

-   New `.return_all_ratios` parameter that allows for returning non-cumulative product density ratios to the user.

-   `bound` parameter renamed to `.bound`.

### Bug Fixes

-   Fixed a bug that caused the final estimate to be incorrectly estimated with SDR (issue \#87).

-   Fixed a bug that outputted outcome regressions and density ratios in incorrect order compared to the original data.

-   Fixed a bug in the missing data check that threw an error for missing data after an observation experiences the outcome.

-   Fixed a bug in the calculation of standard errors when the `id` parameter is specified.

-   Fixed a bug that resulted in `NA` censoring indicators throwing an error for missing data.

-   Fixed a bug about `values()` being deprecated in the **future** package (issue \#82).

-   Fixed a warning from the **future** package regarding random number generation (issue \#81).

-   Fixed `create_node_list()` returns description (issue \#77).

### Dependencies

-   **slider** dependency removed.

-   **data.table** added as a dependency.

### General

-   `event_locf()` speed greatly improved (issue \#80).

-   Migrated continuous integration from Travis-CI to GitHub Actions.

-   Added a `NEWS.md` file to track changes to the package.

-   License change to GPL-3.
