# bmlm 1.3.5

- Fix (harmless) constructor error message

# bmlm 1.3.4

- Minor cleaning of Stan code
- Fix typos in documentation

# bmlm 1.3.3

- Change the label ‘%me’ to ‘pme’ (for proportion mediated effect) in output of mlm_path_plot(…, text = TRUE).

# bmlm 1.3.2

- Add options to
`mlm_spaghetti_plot()`

to allow jittering and adjusting size of the error bars.

# bmlm 1.3.1

`mlm_spaghetti_plot()`

now has argument `mx`

which can be set to `mx = "data"`

to plot the spaghetti plot of the M - Y relationship (b path) such that the X values are from data, and not fitted values from the X - M model (a path). The argument defaults to `mx = "fitted"`

, such that the X axis values of the M - Y spaghetti plot are fitted values.

# bmlm 1.3.0

- New function
`mlm_spaghetti_plot()`

for visualizing model-fitted values for paths a (X->M regression) and b (M->Y regression)

# bmlm 1.2.10

- Default priors are now
*N**o**r**m**a**l*(0, 1000) for regression coefficients, and *C**a**u**c**h**y*(0, 50) for group-level SDs
`mlm_summary()`

now gives only population level parameters by default, and group-level parameters when `pars = "random"`

- Renamed the mediated effect parameter to
*me* to distinguish it from the product of *a* and *b* (similarly for group-level *u_me*)
`mlm_path_plot()`

now draws a template if no model is entered (i.e. `template`

argument is deprecated)
`mlm_path_plot()`

now by default also shows SDs of group-level effects. This behavior can be turned off by specifying `random = FALSE`

- The fitted model object doesn’t contain the whole covariance matrix anymore, but now contains the group-level intercepts
- New example data set included in package:
`MEC2010`

- Posterior standard deviation is now referred to as SE in
`mlm_summary()`

# bmlm 1.2.9

Removed sigma_y from being modeled when binary_y = TRUE.

# bmlm 1.2.1

Removed posterior probabilities from default outputs.

Added type = “violin” as option for plotting coefficients with mlm_pars_plot().

# bmlm 1.2.0

Users may now change each individual regression parameter’s prior, instead of classes of priors.

Users may now change the shape parameter of the LKJ prior.

# bmlm 1.1.1

Coefficient plots now reorder parameter estimates, if user has requested varying effects.

Path plot now by default does not scale the edges.

# bmlm 1.1.0

## Major update

bmlm now uses pre-compiled C++ code for the Stan models, which eliminates the need to compile a model each time `mlm()`

is run. This significantly speeds up model estimation.

## Minor update

The Stan code used by `mlm()`

is now built from separate chunks, allowing more flexible and robust model development.

# bmlm 1.0.0

Initial release to CRAN.