Table 8 Logistic regression model summary.
From: The impact of artificial intelligence on accounting practices: an academic perspective
Predictor | Coefficient | Std. Error | z-value | p-value | 95% CI Lower | 95% CI Upper |
|---|---|---|---|---|---|---|
Intercept | −1.1252 | 2.286 | −0.492 | 0.623 | −5.605 | 3.354 |
Q1Ege | −0.2462 | 0.395 | −0.623 | 0.533 | −1.02 | 0.528 |
Q2Gender | −2.2133 | 1.756 | −1.261 | 0.207 | −5.654 | 1.228 |
Q3Educa | −0.0627 | 0.321 | −0.195 | 0.845 | −0.693 | 0.567 |
Q4Exper | 0.1749 | 0.3 | 0.582 | 0.560 | −0.414 | 0.764 |
Q6AI-ues | 0.8637 | 1.102 | 0.783 | 0.433 | −1.297 | 3.024 |
Q7AI-UnLev | −0.0684 | 0.244 | −0.28 | 0.780 | −0.548 | 0.411 |
Q8AI-Pors | 0.332 | 0.357 | 0.931 | 0.352 | −0.367 | 1.031 |
Q9AI-Cons | 0.0764 | 0.311 | 0.245 | 0.806 | −0.534 | 0.686 |
Q10AI-Rep-Use | 0.4522 | 0.261 | 1.73 | 0.084 | −0.06 | 0.965 |
