PWS Autonomy, Competence, Immersion and Well-being 3D plots
Leon Anema
2025-05-26
Mediation Analysis with Interactive Graphs for 3D Visualization
## lavaan 0.6-19 ended normally after 1 iteration
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## Estimator ML
## Optimization method NLMINB
## Number of model parameters 7
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## Number of observations 5047
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## Model Test User Model:
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## Test statistic 0.000
## Degrees of freedom 0
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## Model Test Baseline Model:
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## Test statistic 7427.758
## Degrees of freedom 5
## P-value 0.000
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## User Model versus Baseline Model:
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## Comparative Fit Index (CFI) 1.000
## Tucker-Lewis Index (TLI) 1.000
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## Loglikelihood and Information Criteria:
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## Loglikelihood user model (H0) 7184.553
## Loglikelihood unrestricted model (H1) 7184.553
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## Akaike (AIC) -14355.105
## Bayesian (BIC) -14309.419
## Sample-size adjusted Bayesian (SABIC) -14331.663
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## Root Mean Square Error of Approximation:
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## RMSEA 0.000
## 90 Percent confidence interval - lower 0.000
## 90 Percent confidence interval - upper 0.000
## P-value H_0: RMSEA <= 0.050 NA
## P-value H_0: RMSEA >= 0.080 NA
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## Standardized Root Mean Square Residual:
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## SRMR 0.000
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## Parameter Estimates:
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## Standard errors Bootstrap
## Number of requested bootstrap draws 5000
## Number of successful bootstrap draws 5000
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## Regressions:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## Wellbeing ~
## Autonmy (A__W) 0.253 0.024 10.610 0.000 0.207 0.301
## Comptnc (C__W) 0.295 0.027 11.052 0.000 0.241 0.347
## Immersion ~
## Autonmy (A__I) 0.551 0.025 22.425 0.000 0.501 0.598
## Comptnc (C__I) 0.320 0.027 11.775 0.000 0.268 0.376
## Wellbeing ~
## Immersn (I__W) 0.281 0.020 14.395 0.000 0.244 0.319
## Std.lv Std.all
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## 0.253 0.250
## 0.295 0.252
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## 0.551 0.526
## 0.320 0.265
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## 0.281 0.290
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## Variances:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## .Wellbeing 0.014 0.000 28.827 0.000 0.013 0.015
## .Immersion 0.014 0.001 24.756 0.000 0.013 0.015
## Std.lv Std.all
## 0.014 0.504
## 0.014 0.455
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## R-Square:
## Estimate
## Wellbeing 0.496
## Immersion 0.545
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## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
## directA 0.253 0.024 10.609 0.000 0.207 0.301
## directC 0.295 0.027 11.051 0.000 0.241 0.347
## indirectA 0.155 0.012 12.689 0.000 0.131 0.180
## indirectC 0.090 0.010 9.030 0.000 0.072 0.111
## totalA 0.408 0.022 18.334 0.000 0.364 0.451
## totalC 0.385 0.027 14.339 0.000 0.332 0.438
## prop_mediatedA 0.380 0.034 11.133 0.000 0.317 0.451
## prop_mediatedC 0.234 0.028 8.369 0.000 0.185 0.295
## Std.lv Std.all
## 0.253 0.250
## 0.295 0.252
## 0.155 0.153
## 0.090 0.077
## 0.408 0.402
## 0.385 0.329
## 0.380 0.380
## 0.234 0.234## Call:psych::corr.test(x = data_ACIM)
## Correlation matrix
## Autonomy Competence Immersion Wellbeing
## Autonomy 1.00 0.71 0.71 0.64
## Competence 0.71 1.00 0.64 0.61
## Immersion 0.71 0.64 1.00 0.63
## Wellbeing 0.64 0.61 0.63 1.00
## Sample Size
## [1] 5047
## Probability values (Entries above the diagonal are adjusted for multiple tests.)
## Autonomy Competence Immersion Wellbeing
## Autonomy 0 0 0 0
## Competence 0 0 0 0
## Immersion 0 0 0 0
## Wellbeing 0 0 0 0
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## Confidence intervals based upon normal theory. To get bootstrapped values, try cor.ci
## raw.lower raw.r raw.upper raw.p lower.adj upper.adj
## Atnmy-Cmptn 0.69 0.71 0.72 0 0.69 0.72
## Atnmy-Immrs 0.70 0.71 0.73 0 0.70 0.73
## Atnmy-Wllbn 0.62 0.64 0.65 0 0.61 0.65
## Cmptn-Immrs 0.62 0.64 0.65 0 0.62 0.66
## Cmptn-Wllbn 0.60 0.61 0.63 0 0.60 0.63
## Immrs-Wllbn 0.61 0.63 0.65 0 0.61 0.65##
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## Table 1
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## Means, standard deviations, and correlations with confidence intervals
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##
## Variable M SD 1 2 3
## 1. Autonomy 0.79 0.17
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## 2. Competence 0.84 0.14 .71**
## [.69, .72]
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## 3. Immersion 0.79 0.17 .71** .64**
## [.70, .73] [.62, .65]
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## 4. Wellbeing 0.75 0.17 .64** .61** .63**
## [.62, .65] [.60, .63] [.61, .65]
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## Note. M and SD are used to represent mean and standard deviation, respectively.
## Values in square brackets indicate the 95% confidence interval.
## The confidence interval is a plausible range of population correlations
## that could have caused the sample correlation (Cumming, 2014).
## * indicates p < .05. ** indicates p < .01.
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3D graph with both Autonomy and Immersion and well-being in it
These graphs are interactable, use your mouse cursor to rotate and zoom the graph.
## wgl
## 1
3D graph with both Competence and Immersion and well-being in it
These graphs are interactable, use your mouse cursor to rotate and zoom the graph.
## wgl
## 3
Checking assumptions for mulitple regression:
## Autonomy Competence Immersion
## 2.607984 2.153916 2.197032