Subscribe to:
Post Comments (Atom)
skip to main |
skip to sidebar
Links to specific topics
(See also under "Labels" at the bottom-left area of this blog)
[ Welcome post ] [ Installation issues ] [ WarpPLS.com ] [ Posts with YouTube links ] [ Model-driven data analytics ] [ PLS-SEM email list ]
Ned Kock
About Me
I am a researcher, software developer, consultant, and college professor. Two of my main areas of research are nonlinear variance-based structural equation modeling, and evolutionary biology as it applies to the study of human-technology interaction. My degrees are in engineering (B.E.E.), computer science (M.S.), and business (Ph.D.). I am interested in the application of science, statistics, and technology to the understanding of human health and behavior. Here I blog about statistics, and more specifically about nonlinear variance-based structural equation modeling and WarpPLS, the first software to enable this type of analysis. My personal web site contains my contact information and freely available articles related to the topic of this blog: nedkock.com.
Ned Kock on the Web
Copyright
The contents of this blog may be used with proper attribution. Most of the issues covered here are also covered in the latest version of the WarpPLS User Manual. Therefore, you can cite the Manual to refer to issues covered here in this blog.
Acknowledgement
Ned Kock gratefully acknowledges that he regularly consults with the most interesting man in the world, especially in connection with complex mathematical problems.
Interesting Links
- Armin Monecke
- Bradley Efron
- Correlation & Causality - Blog
- Factor Analysis by R.J. Rummel
- Gaston Sanchez
- James E. Gaskin
- Judea Pearl - Publications
- Jörg Henseler - Research
- Overfitting - Wikipedia
- PLS Path Modeling with R (Gaston Sanchez)
- PLS Regression - Wikipedia
- PLS Regression by D. Garson
- PLS-Graph
- PLS-SEM.com
- PLS-School.com
- Ross Ihaka
- SEM - Wikipedia
- SEM by D. Garson
- Sewall Wright - Wikipedia
- SmartPLS
- StatWiki (James E. Gaskin)
- T.K. (Theo) Dijkstra - Research
- VisualPLS
- WarpPLS
- Wolfram Alpha
- Wynne W. Chin
- semPLS: SEM using PLS in R (Armin Monecke)
Labels
- 2D graph (3)
- 3D graph (2)
- action research (1)
- AFVIF (1)
- analytic composite (2)
- ANCOVA (1)
- ANOVA (1)
- APC (2)
- ARS (3)
- AVE (1)
- AVIF (2)
- Baron and Kenny (2)
- Bayes' theorem (1)
- bitcoin (1)
- bootstrapping (7)
- categorical variable (3)
- categorical-to-numeric conversion (1)
- causality assessment (2)
- collinearity (8)
- comma-delimited file (1)
- common method bias (6)
- common structural variation reduction (1)
- comparison of means (3)
- composites (5)
- conditional probabilistic queries (3)
- conditional probabilities (1)
- conference (12)
- confidence interval (1)
- consistent PLS (1)
- constrained latent growth (1)
- control variable (5)
- convergent validity (1)
- correlation (4)
- covariance-SEM (2)
- Cronbach’s alpha (1)
- cross-loadings (3)
- data imputation (1)
- data label (2)
- data segmentation (2)
- descriptive statistics (3)
- dichotomous variables (4)
- Dijkstra's consistent PLS (1)
- Dijkstra's PLSc reliability (1)
- Dijkstra's rho_a (2)
- discriminant validity (3)
- distinct observations (3)
- distinct values (1)
- Dr. Boo (1)
- Durbin–Wu–Hausman test (1)
- e-collaboration (2)
- effect size (1)
- endogeneity (8)
- endogenous dichotomous variables (3)
- endogenous variables (1)
- Excel (2)
- exploratory analysis (1)
- factor reliability (2)
- factor-based PLS (9)
- Factor-based SEM (7)
- factors (5)
- FCVIF (1)
- field research (1)
- field study (1)
- FIMIX-PLS (1)
- fit index (5)
- formative (7)
- formative latent variable (1)
- fractional split (2)
- free questionnaires (1)
- full collinearity variance inflation factors (1)
- full latent growth (6)
- full latent growth coefficients (2)
- gamma-exponential method (1)
- GoF (1)
- graph rotation (2)
- graphs with segments (3)
- group samples (2)
- Harman’s single factor test (2)
- Hausman test (1)
- health data (2)
- highest FCVIF test (4)
- HTMT (2)
- HTMT2 (2)
- hypothesis testing (1)
- India (1)
- indicator (4)
- indicator correlation matrix (2)
- indicator name (1)
- indirect effects (4)
- inner model (2)
- Installation issues (5)
- instrumental variable (7)
- intervening variable (3)
- inverse square root method (1)
- J curve (4)
- jackknifing (6)
- journal article (2)
- kurtosis (1)
- label (2)
- latent growth (4)
- latent variable (6)
- lateral collinearity (1)
- listwise deletion (1)
- loadings (6)
- logistic function (2)
- logistic regression (5)
- Lohmöller (1)
- Mac (1)
- Mac OS (1)
- Malaysia (2)
- marketing (1)
- MATLAB Compiler Runtime (2)
- MDDA (1)
- measurement invariance (3)
- mediating effect (8)
- mediating variable (4)
- mediation (2)
- minimum sample size (4)
- missing data (1)
- missing data imputation (2)
- Model-driven data analytics (MDDA) (2)
- moderated mediation (2)
- moderating effect (12)
- Monte Carlo simulation (3)
- multi-group analysis (7)
- multilevel analysis (3)
- multiple regression (3)
- multivariate normality (1)
- Nicholas Danks (1)
- NLBCDR (1)
- non-normal data (2)
- non-recursive (1)
- nonlinear relationship (18)
- nonlinear theorizing (2)
- number of different values (2)
- number punctuation (1)
- numeric variable (2)
- numeric-to-categorical conversion (1)
- one group and one condition (1)
- one group and two conditions (1)
- one-tailed (2)
- online training (2)
- outer model (1)
- P value (8)
- pairwise deletion (1)
- path analysis (2)
- path coefficient (9)
- PLS Applications Symposium (17)
- PLS regression (4)
- PLS-SEM (10)
- PLS-SEM email distribution list (1)
- PLSc (1)
- PLSF (2)
- png file (1)
- pooled standard error (1)
- power (2)
- Preacher and Hayes (1)
- Preacher and Hayes (1)
- probabilistic queries (2)
- probabilities (3)
- project file (2)
- raw data (1)
- reciprocal relationship (4)
- recursive (1)
- reflective (5)
- reliability (6)
- resampling (5)
- rho_a (2)
- robust multiple regression (5)
- robust path analysis (2)
- robustness tests (1)
- RSCR (1)
- S curve (3)
- sample dataset (1)
- Satterthwaite method (1)
- SChS (1)
- second order latent variable (6)
- segmentation delta (1)
- segmentation delta method (1)
- SEM (2)
- SET PATH (2)
- Simpson's paradox (1)
- Simpson’s paradox (3)
- skewness (1)
- small sample (2)
- SMAR (1)
- Sobel method (1)
- SPR (1)
- SRMR (1)
- SSR (1)
- stable (1)
- standard error (1)
- standardized partial regression coefficient (2)
- stata (2)
- statistical power (4)
- statistical suppression (1)
- STDCR (1)
- STDSR (1)
- stochastic instrumental variable (1)
- structural equation modeling (18)
- sub-samples (1)
- subsamples (1)
- System.sys file (1)
- T ratio (1)
- T value (1)
- tab-delimited file (1)
- The University of Texas at El Paso (1)
- time series (1)
- time series data (1)
- total effects (1)
- training (29)
- true composite reliability (2)
- two-tailed (2)
- type I error (3)
- type II error (3)
- U curve (4)
- univariate normality (1)
- validity (5)
- variance inflation factor (5)
- VIF (2)
- virtual machine (1)
- virtualization (1)
- VMware (1)
- Warp2 regression (3)
- Warp3 regression (3)
- warping (4)
- warppls (104)
- warppls 2.0 (3)
- warppls 3.0 (6)
- warppls 4.0 (4)
- warppls 5.0 (3)
- warppls 6.0 (14)
- warppls 7.0 (2)
- warppls 8.0 (3)
- warppls history (2)
- weights (3)
- Windows 7 (1)
- Windows Vista (1)
- Wold (1)
- Word (1)
- workshop (10)
- XLSTAT incompatibility (1)
- YouTube video (37)
2 comments:
Thank you for good tutorial ...how about multicoliniarity, autocorrelation and normality..i need more understanding in warppls
Hi Hanif. Multicolinearity can be assessed via FCVIFs. Deviations from normality are not a problem in WarpPLS. Autoregression can be addressed through instrumental variables that control for time, employing the anchor-factorial with variation diffusion approach (see links below).
https://warpinvestor.blogspot.com/2020/11/understanding-price-of-bitcoin-data.html
https://scriptwarp.com/dapj/2020_DAPJ_1_2/Kock_2020_DAPJ_1_2_MultiLevel.pdf
On the first link, which is for a newer post on bitcoin, see the discussion on the "iGBTC variable".
Post a Comment