The goal of this package is to provide all necessary tools for
analyses of clinical significance in clinical intervention studies. In
contrast to *statistical* significance, which assesses if it is
probable that there is a treatment effect, *clinical*
significance can be used to determine if a treatment effect is of
practical use or meaningful for patients.

You can install the development version of clinicalsignificance from GitHub with:

```
# install.packages("devtools")
::install_github("pedscience/clinicalsignificance") devtools
```

Given a tidy dataset, the employed instrument’s reliability and
descriptives (*M* and *SD*) of the functional population,
the clinical significance in a study can be easily assessed.

```
library(clinicalsignificance)
<- claus_2020 %>%
results clinical_significance(
id = id,
time = time,
outcome = bdi,
pre = 1,
post = 4,
reliability = 0.81,
m_functional = 8,
sd_functional = 8,
type = "c"
)
results#> Clinical Significance Results (JT)
#>
#> Category | n | Percent
#> ---------------------------
#> Recovered | 10 | 0.250
#> Improved | 9 | 0.225
#> Unchanged | 21 | 0.525
#> Deteriorated | 0 | 0.000
#> Harmed | 0 | 0.000
```

You can receive a detailed summary of the analysis by

```
summary(results)
#>
#> Clinical Significance Results
#>
#> There were 43 participants in the whole dataset of which 40 (93%)
#> could be included in the analysis.
#>
#> The JT method for calculating cutoffs and reliable change was chosen
#> and the outcome variable was "bdi".
#>
#> The cutoff type was "c" with a value of 21.6 based on the following
#> population characteristics (with lower values representing a
#> beneficial outcome):
#>
#> Population Characteristics
#>
#> M Clinical | SD Clinical | M Functional | SD Functional
#> -------------------------------------------------------
#> 35.48 | 8.16 | 8 | 8
#>
#>
#> The instrument's reliability was set to 0.81
#>
#> Individual Level Results
#>
#> Category | n | Percent
#> ---------------------------
#> Recovered | 10 | 0.250
#> Improved | 9 | 0.225
#> Unchanged | 21 | 0.525
#> Deteriorated | 0 | 0.000
#> Harmed | 0 | 0.000
```

or plot the results with

`plot(results)`

Jacobson et al. (1984) criticized, along with other researchers, that the vast majority of research in psychological intervention research is based on statistical significance testing. This procedure comes with two major disadvantages: first, treatment effects are based on groups and lack information on individual participants. Second, a significance test lacks practical relevance. One can think of a hypothetical intervention that expands life expectancy by 1 day. With enough participants incorporated in a significance test, one can virtually guarantee a significant result although most would agree that such an intervention lacks practical relevance.

Therefore, Jacobson et al. (1984) postulated an additional procedure
that categorizes each patient based on his/her individual change. If a
patient (reliably) moves from the dysfunctional to a functional
population, this patient’s change is **clinically
significant**. This case is depicted in the figure below.

Let’s suppose an instrument assessing depressive symptoms. A clinical
population of patients with a major depression may score on average with
*M* = 34 and an *SD* = 8 on this instrument. A functional
population (in this case a sample of people without a major depression)
may score on average with *M* = 8 and an *SD* = 8 on that
same instrument. If now an individual patient with major depression
scores 32 on the depression instrument before and intervention (black
point in the clinical population) and 12 after an intervention (black
point in the functional population) and therefore has crossed the cutoff
between the two populations (the black line in between), then this
patient has changed clinically significant (if that change is beyond the
error of measurement of the instrument).

Jacobson, N. S., Follette, W. C., & Revenstorf, D. (1984). Psychotherapy outcome research: Methods for reporting
variability and evaluating clinical significance. *Behavior
Therapy*, *15*(4), 336–352. https://doi.org/10.1016/S0005-7894(84)80002-7