Free tool that turns a simple, multiple or hierarchical linear regression into an APA 7 or Vancouver table, with "Copy for Word" (it keeps the APA rules: top, below the header and bottom, no vertical lines), a .docx download and the results-section sentence in English and Spanish. It accepts the SPSS "Coefficients" table pasted as is (comma or point decimals, "(Constante)" or "(Constant)"); you type the R² of each block and, given the sample size, it computes ΔR², the F change ΔF = ((R²B − R²A)/df1) / ((1 − R²B)/df2) with df1 = added predictors and df2 = n − k − 1 (Cohen et al., 2003; the "F Change" of SPSS), the 95% CIs of B (B ± critical t × SE) and any missing p values from t = B/SE.
Worked example: predicting the academic performance of n = 150 students in two steps. Step 1 (study hours): R² = .18, F(1, 148) = 32.49, p < .001. Step 2 (adds test anxiety and self-efficacy): R² = .34, ΔR² = .16, ΔF(2, 146) = 17.70, p < .001: the second step significantly improves the model. Final-model coefficients: study hours B = 0.28, 95% CI [0.16, 0.40], β = .34, p < .001; test anxiety B = −0.19 [−0.33, −0.05], β = −.21, p = .007; self-efficacy B = 0.31 [0.13, 0.49], β = .26, p < .001.
Why does ΔF need the sample size? Because its degrees of freedom depend on n (df2 = n − k − 1); without n the table still comes out with B, SE, β and ΔR², but without ΔF or 95% CIs. Do the 95% CIs match SPSS? Yes, up to rounding: they are computed as B ± critical t × SE with the residual degrees of freedom of each block (with df = 96 the critical t is 1.985), which is exactly what SPSS does when you tick Statistics → Confidence intervals.
Turn your simple, multiple or hierarchical regression into an APA 7 or Vancouver table: ΔR², ΔF, 95% CIs and a results sentence. Paste from SPSS, copy to Word.