| Model Info | ||
|---|---|---|
| Info | ||
| Model Type | Mixed Model | Linear Mixed model for continuous y |
| Model | lmer | PlayerLoad ~ 1 + Location + TrainingZone + Location:TrainingZone + ( 1 | ID_jugadora ) |
| Distribution | Gaussian | Normal distribution of residuals |
| Direction | y | Dependend variable scores |
| Optimizer | bobyqa | |
| DF method | Satterthwaite | |
| Sample size | 1626 | |
| Converged | yes | |
| Y transform | none | |
| C.I. method | Wald | |
| [3] | ||
| Model Fit | ||||
|---|---|---|---|---|
| Type | R² | df | LRT X² | p |
| Conditional | 0.915 | 30 | 3875.104 | <.001 |
| Marginal | 0.825 | 29 | 3843.909 | <.001 |
| [4] | ||||
| Fixed Effects Omnibus Tests | ||||
|---|---|---|---|---|
| F | df | df (res) | p | |
| Location | 497.5 | 5 | 1589 | <.001 |
| TrainingZone | 744.2 | 4 | 1590 | <.001 |
| Location ✻ TrainingZone | 11.6 | 20 | 1589 | <.001 |
| Parameter Estimates (Fixed coefficients) | ||||||||
|---|---|---|---|---|---|---|---|---|
| 95% Confidence Intervals | ||||||||
| Names | Effect | Estimate | SE | Lower | Upper | df | t | p |
| (Intercept) | (Intercept) | 0.08417 | 0.0666 | -0.0465 | 0.2149 | 7.23 | 1.2632 | 0.246 |
| Location1 | LK - LA | -0.17652 | 0.0331 | -0.2415 | -0.1115 | 1589.05 | -5.3290 | <.001 |
| Location2 | LS - LA | -0.78624 | 0.0328 | -0.8506 | -0.7218 | 1589.00 | -23.9433 | <.001 |
| Location3 | RA - LA | 0.10737 | 0.0306 | 0.0474 | 0.1674 | 1589.09 | 3.5102 | <.001 |
| Location4 | RK - LA | -0.17179 | 0.0328 | -0.2362 | -0.1074 | 1589.00 | -5.2316 | <.001 |
| Location5 | TS - LA | -1.17654 | 0.0328 | -1.2410 | -1.1121 | 1589.00 | -35.8292 | <.001 |
| TrainingZone1 | R1 - R0 | 0.22013 | 0.0450 | 0.1318 | 0.3085 | 1589.51 | 4.8885 | <.001 |
| TrainingZone2 | R2 - R0 | 0.44397 | 0.0432 | 0.3593 | 0.5287 | 1589.50 | 10.2822 | <.001 |
| TrainingZone3 | R3 - R0 | 0.71749 | 0.0431 | 0.6329 | 0.8021 | 1589.75 | 16.6362 | <.001 |
| TrainingZone4 | R4 - R0 | 0.99238 | 0.0431 | 0.9079 | 1.0769 | 1589.67 | 23.0312 | <.001 |
| Location1 ✻ TrainingZone1 | (LK - LA) ✻ (R1 - R0) | 0.04702 | 0.1571 | -0.2612 | 0.3552 | 1589.00 | 0.2993 | 0.765 |
| Location2 ✻ TrainingZone1 | (LS - LA) ✻ (R1 - R0) | 0.00803 | 0.1569 | -0.2997 | 0.3158 | 1589.00 | 0.0512 | 0.959 |
| Location3 ✻ TrainingZone1 | (RA - LA) ✻ (R1 - R0) | -0.51818 | 0.1435 | -0.7997 | -0.2367 | 1589.02 | -3.6103 | <.001 |
| Location4 ✻ TrainingZone1 | (RK - LA) ✻ (R1 - R0) | -0.05998 | 0.1569 | -0.3677 | 0.2478 | 1589.00 | -0.3823 | 0.702 |
| Location5 ✻ TrainingZone1 | (TS - LA) ✻ (R1 - R0) | -0.21961 | 0.1569 | -0.5274 | 0.0882 | 1589.00 | -1.3996 | 0.162 |
| Location1 ✻ TrainingZone2 | (LK - LA) ✻ (R2 - R0) | 0.21011 | 0.1516 | -0.0872 | 0.5074 | 1589.00 | 1.3861 | 0.166 |
| Location2 ✻ TrainingZone2 | (LS - LA) ✻ (R2 - R0) | -0.00658 | 0.1511 | -0.3030 | 0.2898 | 1589.00 | -0.0435 | 0.965 |
| Location3 ✻ TrainingZone2 | (RA - LA) ✻ (R2 - R0) | -0.45955 | 0.1365 | -0.7273 | -0.1918 | 1589.02 | -3.3669 | <.001 |
| Location4 ✻ TrainingZone2 | (RK - LA) ✻ (R2 - R0) | 0.14534 | 0.1511 | -0.1510 | 0.4417 | 1589.00 | 0.9618 | 0.336 |
| Location5 ✻ TrainingZone2 | (TS - LA) ✻ (R2 - R0) | -0.17737 | 0.1511 | -0.4738 | 0.1190 | 1589.00 | -1.1738 | 0.241 |
| Location1 ✻ TrainingZone3 | (LK - LA) ✻ (R3 - R0) | 0.16425 | 0.1499 | -0.1297 | 0.4582 | 1589.00 | 1.0958 | 0.273 |
| Location2 ✻ TrainingZone3 | (LS - LA) ✻ (R3 - R0) | -0.17760 | 0.1496 | -0.4710 | 0.1158 | 1589.00 | -1.1875 | 0.235 |
| Location3 ✻ TrainingZone3 | (RA - LA) ✻ (R3 - R0) | -0.45211 | 0.1348 | -0.7166 | -0.1876 | 1589.03 | -3.3527 | <.001 |
| Location4 ✻ TrainingZone3 | (RK - LA) ✻ (R3 - R0) | 0.16617 | 0.1496 | -0.1272 | 0.4595 | 1589.00 | 1.1111 | 0.267 |
| Location5 ✻ TrainingZone3 | (TS - LA) ✻ (R3 - R0) | -0.33737 | 0.1496 | -0.6307 | -0.0440 | 1589.00 | -2.2558 | 0.024 |
| Location1 ✻ TrainingZone4 | (LK - LA) ✻ (R4 - R0) | 0.04681 | 0.1503 | -0.2480 | 0.3416 | 1589.00 | 0.3114 | 0.756 |
| Location2 ✻ TrainingZone4 | (LS - LA) ✻ (R4 - R0) | -0.32891 | 0.1499 | -0.6230 | -0.0349 | 1589.00 | -2.1940 | 0.028 |
| Location3 ✻ TrainingZone4 | (RA - LA) ✻ (R4 - R0) | -0.40855 | 0.1352 | -0.6737 | -0.1434 | 1589.03 | -3.0224 | 0.003 |
| Location4 ✻ TrainingZone4 | (RK - LA) ✻ (R4 - R0) | 0.10905 | 0.1499 | -0.1850 | 0.4031 | 1589.00 | 0.7274 | 0.467 |
| Location5 ✻ TrainingZone4 | (TS - LA) ✻ (R4 - R0) | -0.44897 | 0.1499 | -0.7430 | -0.1549 | 1589.00 | -2.9949 | 0.003 |
| [5] | ||||||||
| Random Components | ||||
|---|---|---|---|---|
| Groups | Name | Variance | SD | ICC |
| ID_jugadora | (Intercept) | 0.0348 | 0.186 | 0.515 |
| Residual | 0.0327 | 0.181 | ||
| Nota. Number of Obs: 1626 , Number of groups: ID_jugadora 8 | ||||
| Estimate Marginal Means - Location ✻ TrainingZone | ||||||
|---|---|---|---|---|---|---|
| 95% Confidence Intervals | ||||||
| Location | TrainingZone | Mean | SE | df | Lower | Upper |
| LA | R0 | -0.11327 | 0.1239 | 84.15 | -0.3597 | 0.13315 |
| LA | R1 | 0.23065 | 0.0761 | 12.27 | 0.0653 | 0.39596 |
| LA | R2 | 0.37871 | 0.0698 | 8.72 | 0.2200 | 0.53744 |
| LA | R3 | 0.71033 | 0.0681 | 7.90 | 0.5529 | 0.86776 |
| LA | R4 | 1.05087 | 0.0685 | 8.08 | 0.8932 | 1.20857 |
| LK | R0 | -0.38342 | 0.1239 | 84.15 | -0.6298 | -0.13701 |
| LK | R1 | 0.00752 | 0.0765 | 12.56 | -0.1584 | 0.17338 |
| LK | R2 | 0.31866 | 0.0709 | 9.27 | 0.1590 | 0.47834 |
| LK | R3 | 0.60442 | 0.0689 | 8.25 | 0.4465 | 0.76238 |
| LK | R4 | 0.82752 | 0.0693 | 8.48 | 0.6692 | 0.98585 |
| LS | R0 | -0.79850 | 0.1239 | 84.15 | -1.0449 | -0.55208 |
| LS | R1 | -0.44654 | 0.0761 | 12.27 | -0.6119 | -0.28123 |
| LS | R2 | -0.31310 | 0.0698 | 8.72 | -0.4718 | -0.15437 |
| LS | R3 | -0.15250 | 0.0681 | 7.90 | -0.3099 | 0.00493 |
| LS | R4 | 0.03673 | 0.0685 | 8.08 | -0.1210 | 0.19443 |
| RA | R0 | 0.36178 | 0.1045 | 43.37 | 0.1510 | 0.57253 |
| RA | R1 | 0.18752 | 0.0781 | 13.61 | 0.0196 | 0.35539 |
| RA | R2 | 0.39420 | 0.0707 | 9.16 | 0.2347 | 0.55367 |
| RA | R3 | 0.73326 | 0.0691 | 8.37 | 0.5751 | 0.89142 |
| RA | R4 | 1.11736 | 0.0694 | 8.50 | 0.9590 | 1.27573 |
| RK | R0 | -0.35718 | 0.1239 | 84.15 | -0.6036 | -0.11076 |
| RK | R1 | -0.07324 | 0.0761 | 12.27 | -0.2386 | 0.09207 |
| RK | R2 | 0.28014 | 0.0698 | 8.72 | 0.1214 | 0.43887 |
| RK | R3 | 0.63259 | 0.0681 | 7.90 | 0.4752 | 0.79002 |
| RK | R4 | 0.91601 | 0.0685 | 8.08 | 0.7583 | 1.07371 |
| TS | R0 | -1.05315 | 0.1239 | 84.15 | -1.2996 | -0.80673 |
| TS | R1 | -0.92884 | 0.0761 | 12.27 | -1.0942 | -0.76353 |
| TS | R2 | -0.73854 | 0.0698 | 8.72 | -0.8973 | -0.57981 |
| TS | R3 | -0.56692 | 0.0681 | 7.90 | -0.7244 | -0.40949 |
| TS | R4 | -0.33798 | 0.0685 | 8.08 | -0.4957 | -0.18029 |
| Test for Normality of residuals | ||
|---|---|---|
| Test | Statistics | p |
| Kolmogorov-Smirnov | 0.0307 | 0.093 |
| Shapiro-Wilk | 0.9967 | 0.001 |
| Nota. ties should not be present for the one-sample Kolmogorov-Smirnov test | ||
[1] The jamovi project (2024). jamovi. (Version 2.6) [Computer Software]. Retrieved from https://www.jamovi.org.
[2] R Core Team (2024). R: A Language and environment for statistical computing. (Version 4.4) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2024-08-07).
[3] Gallucci, M. (2019). GAMLj: General analyses for linear models. [jamovi module]. Retrieved from https://gamlj.github.io/.
[4] Gallucci, M. (2020). Model goodness of fit in GAMLj. . link.
[5] Lüdecke, Ben-Shachar, Patil & Makowski (2020). Extracting, Computing and Exploring the Parameters of Statistical Models using R. CRAN. link.