ai_distress

Meta-analayis of RCTs evaluating the effect of AI agents to reduce psychological distress
effects

Provides a new class of Bayesian meta-analysis models that incorporates a model for internal and external validity bias. In this way, it is possible to combine studies of diverse quality and different types. For example, we can combine the results of randomized control trials (RCTs) with the results of observational studies (OS).

Pablo Emilio Verde

jarbes

Just a Rather Bayesian Evidence Synthesis

ai_distress function

A data frame with 21 RCT studies
#'<dl>
 <dt>study_id</dt>
<dd>Study identifier.</dd> <dt>TE</dt>
<dd>Treatment effect reported; standardized mean difference with
 Hedges small-sample correction (Hedges' g).</dd> <dt>seTE</dt>
<dd>Standard error of <code>TE</code>, derived from the plotted 95% confidence interval using <code>seTE = (upper - lower) / (2 * 1.96)</code>. Confidence intervals are not stored.</dd> <dt>risk_of_bias</dt>
<dd>Overall Risk of Bias assessment reported in the plot (<code>"Low risk of bias"</code>, <code>"Some concerns"</code>, <code>"High risk of bias"</code>).</dd>
</dl>

Format

Meta-analayis of RCTs evaluating the effect of AI agents to reduce psychological distress
effects — ai_distress

A data frame with 21 RCT studies
#'<dl>
 <dt>study_id</dt>
<dd>Study identifier.</dd>

 <dt>TE</dt>
<dd>Treatment effect reported; standardized mean difference with
 Hedges small-sample correction (Hedges' g).</dd>

 <dt>seTE</dt>
<dd>Standard error of <code>TE</code>, derived from the plotted 95% confidence interval using <code>seTE = (upper - lower) / (2 * 1.96)</code>. Confidence intervals are not stored.</dd>

 <dt>risk_of_bias</dt>
<dd>Overall Risk of Bias assessment reported in the plot (<code>"Low risk of bias"</code>, <code>"Some concerns"</code>, <code>"High risk of bias"</code>).</dd>


</dl>

ai_distress: Meta-analayis of RCTs evaluating the effect of AI agents to reduce psychological distress effects

Description

Arguments

Format