falkcarl/multilevelmediation
Utility Functions for Multilevel Mediation Analysis

Package index
Search the falkcarl/multilevelmediation package
Vignettes
Functions
24
Source code
12
Man pages
11
Home
/
GitHub
/
falkcarl/multilevelmediation
/
tests/testthat/_snaps/modmedmlm.md

tests/testthat/_snaps/modmedmlm.md
In falkcarl/multilevelmediation: Utility Functions for Multilevel Mediation Analysis

BPG rand a rand b

Code
  extract.modmed.mlm(fit)
Output
            Sm           Sy          SmX          SyX          SyM      re.SmSm 
   0.096021954 -0.093772127  0.612020371  0.244975365  0.588036915  0.698044627 
       re.SySm     re.SmXSm     re.SyMSm      re.SmSy      re.SySy     re.SmXSy 
   0.050825005  0.017486251  0.008367895  0.050825005  0.276507737  0.012162696 
      re.SyMSy     re.SmSmX     re.SySmX    re.SmXSmX    re.SyMSmX     re.SmSyM 
  -0.013223201  0.017486251  0.012162696  0.120767200  0.092542236  0.008367895 
      re.SySyM    re.SmXSyM    re.SyMSyM 
  -0.013223201  0.092542236  0.134700854

Code
  extract.modmed.mlm(fit, type = "indirect")
Output
  [1] 0.4524328

Code
  extract.modmed.mlm(fit, type = "a")
Output
  [1] 0.6120204

Code
  extract.modmed.mlm(fit, type = "b")
Output
  [1] 0.5880369

Code
  extract.modmed.mlm(fit, type = "covab")
Output
  [1] 0.09254224

Code
  extract.modmed.mlm(fit, type = "cprime")
Output
  [1] 0.2449754

Code
  extract.modmed.mlm(fit, type = "fixef")
Output
           Sm          Sy         SmX         SyX         SyM 
   0.09602195 -0.09377213  0.61202037  0.24497536  0.58803691

Code
  extract.modmed.mlm(fit, type = "recov")
Output
               Sm         Sy        SmX          SyM
  Sm  0.698044627  0.0508250 0.01748625  0.008367895
  Sy  0.050825005  0.2765077 0.01216270 -0.013223201
  SmX 0.017486251  0.0121627 0.12076720  0.092542236
  SyM 0.008367895 -0.0132232 0.09254224  0.134700854

Code
  extract.modmed.mlm(fit, type = "recov.vec")
Output
       re.SmSm      re.SySm     re.SmXSm     re.SyMSm      re.SmSy      re.SySy 
   0.698044627  0.050825005  0.017486251  0.008367895  0.050825005  0.276507737 
      re.SmXSy     re.SyMSy     re.SmSmX     re.SySmX    re.SmXSmX    re.SyMSmX 
   0.012162696 -0.013223201  0.017486251  0.012162696  0.120767200  0.092542236 
      re.SmSyM     re.SySyM    re.SmXSyM    re.SyMSyM 
   0.008367895 -0.013223201  0.092542236  0.134700854

BPG rand a, rand b, rand c

Code
  extract.modmed.mlm(fit)
Output
            Sm           Sy          SmX          SyX          SyM      re.SmSm 
   0.092678783 -0.097198953  0.611892535  0.219355102  0.611766783  0.677715547 
       re.SySm     re.SmXSm     re.SyMSm     re.SyXSm      re.SmSy      re.SySy 
   0.056226656  0.018587977  0.009326583 -0.005992485  0.056226656  0.271354193 
      re.SmXSy     re.SyMSy     re.SyXSy     re.SmSmX     re.SySmX    re.SmXSmX 
   0.012226000 -0.004331612 -0.017460059  0.018587977  0.012226000  0.120100414 
     re.SyMSmX    re.SyXSmX     re.SmSyM     re.SySyM    re.SmXSyM    re.SyMSyM 
   0.099872640 -0.022766909  0.009326583 -0.004331612  0.099872640  0.110314811 
     re.SyXSyM     re.SmSyX     re.SySyX    re.SmXSyX    re.SyMSyX    re.SyXSyX 
   0.007044345 -0.005992485 -0.017460059 -0.022766909  0.007044345  0.030512781

Code
  extract.modmed.mlm(fit, type = "indirect")
Output
  [1] 0.4742082

Code
  extract.modmed.mlm(fit, type = "a")
Output
  [1] 0.6118925

Code
  extract.modmed.mlm(fit, type = "b")
Output
  [1] 0.6117668

Code
  extract.modmed.mlm(fit, type = "covab")
Output
  [1] 0.09987264

Code
  extract.modmed.mlm(fit, type = "cprime")
Output
  [1] 0.2193551

Code
  extract.modmed.mlm(fit, type = "fixef")
Output
           Sm          Sy         SmX         SyX         SyM 
   0.09267878 -0.09719895  0.61189254  0.21935510  0.61176678

Code
  extract.modmed.mlm(fit, type = "recov")
Output
                Sm           Sy         SmX          SyM          SyX
  Sm   0.677715547  0.056226656  0.01858798  0.009326583 -0.005992485
  Sy   0.056226656  0.271354193  0.01222600 -0.004331612 -0.017460059
  SmX  0.018587977  0.012226000  0.12010041  0.099872640 -0.022766909
  SyM  0.009326583 -0.004331612  0.09987264  0.110314811  0.007044345
  SyX -0.005992485 -0.017460059 -0.02276691  0.007044345  0.030512781

Code
  extract.modmed.mlm(fit, type = "recov.vec")
Output
       re.SmSm      re.SySm     re.SmXSm     re.SyMSm     re.SyXSm      re.SmSy 
   0.677715547  0.056226656  0.018587977  0.009326583 -0.005992485  0.056226656 
       re.SySy     re.SmXSy     re.SyMSy     re.SyXSy     re.SmSmX     re.SySmX 
   0.271354193  0.012226000 -0.004331612 -0.017460059  0.018587977  0.012226000 
     re.SmXSmX    re.SyMSmX    re.SyXSmX     re.SmSyM     re.SySyM    re.SmXSyM 
   0.120100414  0.099872640 -0.022766909  0.009326583 -0.004331612  0.099872640 
     re.SyMSyM    re.SyXSyM     re.SmSyX     re.SySyX    re.SmXSyX    re.SyMSyX 
   0.110314811  0.007044345 -0.005992485 -0.017460059 -0.022766909  0.007044345 
     re.SyXSyX 
   0.030512781

BPG rand a

Code
  extract.modmed.mlm(fit)
Output
            Sm           Sy          SmX          SyX          SyM      re.SmSm 
   0.094696305 -0.122614503  0.611216790  0.284494102  0.685198220  0.708110737 
       re.SySm     re.SmXSm      re.SmSy      re.SySy     re.SmXSy     re.SmSmX 
   0.049550703  0.007702409  0.049550703  0.417115234 -0.007002409  0.007702409 
      re.SySmX    re.SmXSmX 
  -0.007002409  0.115591134

Code
  extract.modmed.mlm(fit, type = "indirect")
Output
  [1] 0.4188047

Code
  extract.modmed.mlm(fit, type = "a")
Output
  [1] 0.6112168

Code
  extract.modmed.mlm(fit, type = "b")
Output
  [1] 0.6851982

Code
  extract.modmed.mlm(fit, type = "cprime")
Output
  [1] 0.2844941

Code
  extract.modmed.mlm(fit, type = "fixef")
Output
          Sm         Sy        SmX        SyX        SyM 
   0.0946963 -0.1226145  0.6112168  0.2844941  0.6851982

Code
  extract.modmed.mlm(fit, type = "recov")
Output
               Sm           Sy          SmX
  Sm  0.708110737  0.049550703  0.007702409
  Sy  0.049550703  0.417115234 -0.007002409
  SmX 0.007702409 -0.007002409  0.115591134

Code
  extract.modmed.mlm(fit, type = "recov.vec")
Output
       re.SmSm      re.SySm     re.SmXSm      re.SmSy      re.SySy     re.SmXSy 
   0.708110737  0.049550703  0.007702409  0.049550703  0.417115234 -0.007002409 
      re.SmSmX     re.SySmX    re.SmXSmX 
   0.007702409 -0.007002409  0.115591134

BPG rand b

Code
  extract.modmed.mlm(fit)
Output
           Sm          Sy         SmX         SyX         SyM     re.SmSm 
   0.07089517 -0.08971709  0.62127750  0.26163174  0.60777762  0.80731942 
      re.SySm    re.SyMSm     re.SmSy     re.SySy    re.SyMSy    re.SmSyM 
   0.04491574 -0.02923504  0.04491574  0.27556755 -0.01777642 -0.02923504 
     re.SySyM   re.SyMSyM 
  -0.01777642  0.13410918

Code
  extract.modmed.mlm(fit, type = "indirect")
Output
  [1] 0.3775986

Code
  extract.modmed.mlm(fit, type = "a")
Output
  [1] 0.6212775

Code
  extract.modmed.mlm(fit, type = "b")
Output
  [1] 0.6077776

Code
  extract.modmed.mlm(fit, type = "cprime")
Output
  [1] 0.2616317

Code
  extract.modmed.mlm(fit, type = "fixef")
Output
           Sm          Sy         SmX         SyX         SyM 
   0.07089517 -0.08971709  0.62127750  0.26163174  0.60777762

Code
  extract.modmed.mlm(fit, type = "recov")
Output
               Sm          Sy         SyM
  Sm   0.80731942  0.04491574 -0.02923504
  Sy   0.04491574  0.27556755 -0.01777642
  SyM -0.02923504 -0.01777642  0.13410918

Code
  extract.modmed.mlm(fit, type = "recov.vec")
Output
      re.SmSm     re.SySm    re.SyMSm     re.SmSy     re.SySy    re.SyMSy 
   0.80731942  0.04491574 -0.02923504  0.04491574  0.27556755 -0.01777642 
     re.SmSyM    re.SySyM   re.SyMSyM 
  -0.02923504 -0.01777642  0.13410918

moderated a

Code
  extract.modmed.mlm(fitmoda, "indirect", modval1 = 0)
Output
  [1] 0.2064048

Code
  extract.modmed.mlm(fitmoda, "indirect", modval1 = 1)
Output
  [1] 0.247949

Code
  extract.modmed.mlm(fitmoda, "indirect.diff", modval1 = 0, modval2 = 1)
Output
  [1] -0.04154419

Code
  extract.modmed.mlm(fitmoda, "indirect", modval1 = 0) - extract.modmed.mlm(
    fitmoda, "indirect", modval1 = 1)
Output
  [1] -0.04154419

Code
  extract.modmed.mlm(fitmoda, "a", modval1 = 0)
Output
  [1] 0.2824572

Code
  extract.modmed.mlm(fitmoda, "a", modval1 = 1)
Output
  [1] 0.3988154

Code
  extract.modmed.mlm(fitmoda, "a.diff", modval1 = 0, modval2 = 1)
Output
  [1] -0.1163582

Code
  extract.modmed.mlm(fitmoda, "a", modval1 = 0) - extract.modmed.mlm(fitmoda, "a",
    modval1 = 1)
Output
  [1] -0.1163582

Code
  extract.modmed.mlm(fitmoda, "b", modval1 = 0)
Output
  [1] 0.3570369

Code
  extract.modmed.mlm(fitmoda, "b", modval1 = 1)
Output
  [1] 0.3570369

Code
  extract.modmed.mlm(fitmoda, "b.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0

Code
  extract.modmed.mlm(fitmoda, "b", modval1 = 0) - extract.modmed.mlm(fitmoda, "b",
    modval1 = 1)
Output
  [1] 0

moderated b

Code
  extract.modmed.mlm(fitmodb, "indirect", modval1 = 0)
Output
  [1] 0.3029866

Code
  extract.modmed.mlm(fitmodb, "indirect", modval1 = 1)
Output
  [1] 0.1880396

Code
  extract.modmed.mlm(fitmodb, "indirect.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.114947

Code
  extract.modmed.mlm(fitmodb, "indirect", modval1 = 0) - extract.modmed.mlm(
    fitmodb, "indirect", modval1 = 1)
Output
  [1] 0.114947

Code
  extract.modmed.mlm(fitmodb, "a", modval1 = 0)
Output
  [1] 0.3466758

Code
  extract.modmed.mlm(fitmodb, "a", modval1 = 1)
Output
  [1] 0.3466758

Code
  extract.modmed.mlm(fitmodb, "a.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0

Code
  extract.modmed.mlm(fitmodb, "a", modval1 = 0) - extract.modmed.mlm(fitmodb, "a",
    modval1 = 1)
Output
  [1] 0

Code
  extract.modmed.mlm(fitmodb, "b", modval1 = 0)
Output
  [1] 0.5390697

Code
  extract.modmed.mlm(fitmodb, "b", modval1 = 1)
Output
  [1] 0.2075004

Code
  extract.modmed.mlm(fitmodb, "b.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.3315693

Code
  extract.modmed.mlm(fitmodb, "b", modval1 = 0) - extract.modmed.mlm(fitmodb, "b",
    modval1 = 1)
Output
  [1] 0.3315693

moderated a and b

Code
  extract.modmed.mlm(fitmodab, "indirect", modval1 = 0)
Output
  [1] 0.2704902

Code
  extract.modmed.mlm(fitmodab, "indirect", modval1 = 1)
Output
  [1] 0.2007316

Code
  extract.modmed.mlm(fitmodab, "indirect.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.06975858

Code
  extract.modmed.mlm(fitmodab, "indirect", modval1 = 0) - extract.modmed.mlm(
    fitmodab, "indirect", modval1 = 1)
Output
  [1] 0.06975858

Code
  extract.modmed.mlm(fitmodab, "a", modval1 = 0)
Output
  [1] 0.283115

Code
  extract.modmed.mlm(fitmodab, "a", modval1 = 1)
Output
  [1] 0.3998554

Code
  extract.modmed.mlm(fitmodab, "a.diff", modval1 = 0, modval2 = 1)
Output
  [1] -0.1167403

Code
  extract.modmed.mlm(fitmodab, "a", modval1 = 0) - extract.modmed.mlm(fitmodab,
    "a", modval1 = 1)
Output
  [1] -0.1167403

Code
  extract.modmed.mlm(fitmodab, "b", modval1 = 0)
Output
  [1] 0.5384096

Code
  extract.modmed.mlm(fitmodab, "b", modval1 = 1)
Output
  [1] 0.206758

Code
  extract.modmed.mlm(fitmodab, "b.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.3316517

Code
  extract.modmed.mlm(fitmodab, "b", modval1 = 0) - extract.modmed.mlm(fitmodab,
    "b", modval1 = 1)
Output
  [1] 0.3316517

moderated a and b rand interaction a

Code
  extract.modmed.mlm(fitmodab2, "indirect", modval1 = 0)
Output
  [1] 0.3088432

Code
  extract.modmed.mlm(fitmodab2, "indirect", modval1 = 1)
Output
  [1] 0.1614151

Code
  extract.modmed.mlm(fitmodab2, "indirect.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.1474281

Code
  extract.modmed.mlm(fitmodab2, "indirect", modval1 = 0) - extract.modmed.mlm(
    fitmodab2, "indirect", modval1 = 1)
Output
  [1] 0.1474281

Code
  extract.modmed.mlm(fitmodab2, "a", modval1 = 0)
Output
  [1] 0.2867552

Code
  extract.modmed.mlm(fitmodab2, "a", modval1 = 1)
Output
  [1] 0.3806712

Code
  extract.modmed.mlm(fitmodab2, "a.diff", modval1 = 0, modval2 = 1)
Output
  [1] -0.09391599

Code
  extract.modmed.mlm(fitmodab2, "a", modval1 = 0) - extract.modmed.mlm(fitmodab2,
    "a", modval1 = 1)
Output
  [1] -0.09391599

Code
  extract.modmed.mlm(fitmodab2, "b", modval1 = 0)
Output
  [1] 0.5325046

Code
  extract.modmed.mlm(fitmodab2, "b", modval1 = 1)
Output
  [1] 0.2099373

Code
  extract.modmed.mlm(fitmodab2, "b.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.3225673

Code
  extract.modmed.mlm(fitmodab2, "b", modval1 = 0) - extract.modmed.mlm(fitmodab2,
    "b", modval1 = 1)
Output
  [1] 0.3225673

moderated a and b rand interaction b

Code
  extract.modmed.mlm(fitmodab3, "indirect", modval1 = 0)
Output
  [1] 0.2928716

Code
  extract.modmed.mlm(fitmodab3, "indirect", modval1 = 1)
Output
  [1] 0.1901704

Code
  extract.modmed.mlm(fitmodab3, "indirect.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.1027011

Code
  extract.modmed.mlm(fitmodab3, "indirect", modval1 = 0) - extract.modmed.mlm(
    fitmodab3, "indirect", modval1 = 1)
Output
  [1] 0.1027011

Code
  extract.modmed.mlm(fitmodab3, "a", modval1 = 0)
Output
  [1] 0.2874954

Code
  extract.modmed.mlm(fitmodab3, "a", modval1 = 1)
Output
  [1] 0.4079777

Code
  extract.modmed.mlm(fitmodab3, "a.diff", modval1 = 0, modval2 = 1)
Output
  [1] -0.1204823

Code
  extract.modmed.mlm(fitmodab3, "a", modval1 = 0) - extract.modmed.mlm(fitmodab3,
    "a", modval1 = 1)
Output
  [1] -0.1204823

Code
  extract.modmed.mlm(fitmodab3, "b", modval1 = 0)
Output
  [1] 0.5946465

Code
  extract.modmed.mlm(fitmodab3, "b", modval1 = 1)
Output
  [1] 0.214396

Code
  extract.modmed.mlm(fitmodab3, "b.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.3802505

Code
  extract.modmed.mlm(fitmodab3, "b", modval1 = 0) - extract.modmed.mlm(fitmodab3,
    "b", modval1 = 1)
Output
  [1] 0.3802505

moderated a and b rand interaction both

Code
  extract.modmed.mlm(fitmodab4, "indirect", modval1 = 0)
Output
  [1] 0.3091309

Code
  extract.modmed.mlm(fitmodab4, "indirect", modval1 = 1)
Output
  [1] 0.1511918

Code
  extract.modmed.mlm(fitmodab4, "indirect.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.1579391

Code
  extract.modmed.mlm(fitmodab4, "indirect", modval1 = 0) - extract.modmed.mlm(
    fitmodab4, "indirect", modval1 = 1)
Output
  [1] 0.1579391

Code
  extract.modmed.mlm(fitmodab4, "a", modval1 = 0)
Output
  [1] 0.2909317

Code
  extract.modmed.mlm(fitmodab4, "a", modval1 = 1)
Output
  [1] 0.3874295

Code
  extract.modmed.mlm(fitmodab4, "a.diff", modval1 = 0, modval2 = 1)
Output
  [1] -0.09649783

Code
  extract.modmed.mlm(fitmodab4, "a", modval1 = 0) - extract.modmed.mlm(fitmodab4,
    "a", modval1 = 1)
Output
  [1] -0.09649783

Code
  extract.modmed.mlm(fitmodab4, "b", modval1 = 0)
Output
  [1] 0.5847626

Code
  extract.modmed.mlm(fitmodab4, "b", modval1 = 1)
Output
  [1] 0.2282696

Code
  extract.modmed.mlm(fitmodab4, "b.diff", modval1 = 0, modval2 = 1)
Output
  [1] 0.356493

Code
  extract.modmed.mlm(fitmodab4, "b", modval1 = 0) - extract.modmed.mlm(fitmodab4,
    "b", modval1 = 1)
Output
  [1] 0.356493


falkcarl/multilevelmediation documentation built on Jan. 11, 2025, 5:16 a.m.

R Package Documentation

rdrr.io home R language documentation Run R code online

Browse R Packages

CRAN packages Bioconductor packages R-Forge packages GitHub packages

We want your feedback!

Note that we can't provide technical support on individual packages. You should contact the package authors for that.
GitHub issue tracker
ian@mutexlabs.com
Personal blog

 
Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.

Close