Plots trends over time

Plots the trend for selected parameters of a model. Can be used either with a p_vector, or trial-wise parameters or covariates obtained from predict()

Usage

plot_trend(
  input_data,
  emc,
  par_name,
  subject = 1,
  filter = NULL,
  on_x_axis = "trials",
  pp_shaded = TRUE,
  ...
)

Arguments

input_data

a p_vector or posterior predictives compatible with the provided emc object

emc

An emc object

par_name

Parameter name (or covariate name) to plot

subject

Subject number to plot

filter

Optional function that takes a data frame and returns a logical vector indicating which rows to include in the plot

on_x_axis

Column name in the dadm to plot on the x-axis. By default 'trials'.

pp_shaded

Boolean. If TRUE will plot 95% credible interval as a shaded area. Otherwise plots separate lines for each iteration of the posterior predictives. Only applicable if input_data are posterior predictives.

...

Optional arguments that can be passed to plots.

Value

A trend plot

Examples

dat <- EMC2:::add_trials(forstmann)
dat$trials2 <- dat$trials/1000

lin_trend <- make_trend(cov_names='trials2',
                        kernels = 'exp_incr',
                        par_names='B',
                        bases='lin',
                        phase = "premap")

design_RDM_lin_B <- design(model=RDM,
                           data=dat,
                           covariates='trials2',   # specify relevant covariate columns
                           matchfun=function(d) d$S==d$lR,
                           transform=list(func=c('B'='identity')),
                           formula=list(B ~ 1, v ~ lM, t0 ~ 1),
                           trend=lin_trend)       # add trend
#> Intercept formula added for trend_pars: B.w, B.d_ei
#> Parameter(s) A, s not specified in formula and assumed constant.
#> 
#>  Sampled Parameters: 
#> [1] "B"        "v"        "v_lMTRUE" "t0"       "B.w"      "B.d_ei"  
#> 
#>  Design Matrices: 
#> $B
#>  B
#>  1
#> 
#> $v
#>     lM v v_lMTRUE
#>   TRUE 1        1
#>  FALSE 1        0
#> 
#> $t0
#>  t0
#>   1
#> 
#> $B.w
#>  B.w
#>    1
#> 
#> $B.d_ei
#>  B.d_ei
#>       1
#> 
#> $A
#>  A
#>  1
#> 
#> $s
#>  s
#>  1
#> 

emc <- make_emc(dat, design=design_RDM_lin_B, compress = FALSE)
#> Processing data set 1
p_vector <- c('B'=1, 'v'=1, 'v_lMTRUE'=1, 't0'=0.1, 'B.w'=1, 'B.d_ei'=1)

# Visualize trend
plot_trend(p_vector, emc=emc,
           par_name='B', subject='as1t',
           filter=function(d) d$lR=='right', main='Threshold for right')