# calibrateItems

##### Determine the optimal scale constant for a set of items

Data are passed through `filterGraph`

and `normalizeData`

.
Then the ‘unidim_adapt’ model is fit to each item individually.
A larger `varCorrection`

will obtain a more accurate
`scale`

, but is also more likely to produce an intractable
model. A good compromise is between 2.0 and 4.0.

##### Usage

```
calibrateItems(df, iter = 2000L, chains = 4L, varCorrection = 3,
maxAttempts = 5L, ...)
```

##### Arguments

- df
a data frame with pairs of vertices given in columns

`pa1`

and`pa2`

, and item response data in other columns- iter
A positive integer specifying the number of iterations for each chain (including warmup).

- chains
A positive integer specifying the number of Markov chains.

- varCorrection
A correction factor greater than or equal to 1.0

- maxAttempts
How many times to try re-running a model with more iterations.

- ...
Additional options passed to

`stan`

. The usual choices are`iter`

for the number of iterations and`chains`

for the number of chains.

##### Value

A data.frame (one row per item) with the following columns:

- item
Name of the item

- iter
Number of iterations per chain

- divergent
Number of divergent transitions observed after warmup

- treedepth
Number of times the treedepth was exceeded

- low_bfmi
Number of chains with low E-BFMI

- n_eff
Minimum effective number of samples across all parameters

- Rhat
Maximum Rhat across all parameters

- scale
Median marginal posterior of

`scale`

- thetaVar
Median variance of theta (latent scores)

##### References

Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., & B<U+00FC>rkner, P. C. (2019). Rank-normalization, folding, and localization: An improved \(\widehat R\) for assessing convergence of MCMC. arXiv preprint arXiv:1903.08008.

##### See Also

##### Examples

```
# NOT RUN {
result <- calibrateItems(phyActFlowPropensity) # takes more than 5 seconds
print(result)
# }
```

*Documentation reproduced from package pcFactorStan, version 0.11, License: GPL (>= 3)*