Joe F. Hair, Jr.Joe F. Hair, Jr.Founder & Senior ScholarFounder & Senior Scholar

Joe F. Hair, Jr.Joe F. Hair, Jr.Founder & Senior ScholarFounder & Senior Scholar

Using the SmartPLS SoftwareUsing the SmartPLS Software

Double click anywhere on this tab to close or bring back the

SmartPLS navigation windows.

More SmartPLS More SmartPLS Options . . .Options . . .

To close the navigation windows on the left side of the screen (for “Projects,” “Outline,” and “Indicators”), double click on the tab (shown above) that has the name of your structural model. Note, do NOT click on the “X” because your structural model will close instead. By closing the navigation windows, you will have a larger area on the screen to display your model. The extra space on the screen is particularly helpful when you have a complex model, when you are trying to get your model to display appropriately to save or copy the image, or when you are assessing the model visually or viewing the SmartPLS reports. To bring the navigation windows back, simply double click on the tab again, and the windows will return.

More SmartPLS More SmartPLS Options . . .Options . . .

To save the SmartPLS model as a To save the SmartPLS model as a ““bitmapbitmap”” (.bmp) image file, select (.bmp) image file, select ““FileFile”” ““Export to ImageExport to Image”” from the from the menu bar (see next slide). menu bar (see next slide).

There are several choices to obtain an image file for your SmartPLS structural model. The first option is to select “File” “Export to Image” from the menu bar, as shown above. This allows you to export a “bitmap” image file (.bmp) of your model exactly as it is shown on the monitor. For example, if you have calculated any of the SmartPLS tasks (i.e., PLS algorithm, FIMIX-PLS, Bootstrapping, or Blindfolding) and the model is labeled with the output of the algorithm, that information will show on the .bmp file. But if your model is not visually appealing on the screen, it will not be visually appealing in the .bmp file. A nice feature of the .bmp option is that your SmartPLS model will appear on a white background, which is generally a better option for printing the image, including it in a PowerPoint presentation, or using the image as part of a journal submission.

Other options are dependent on your computer’s software or operating system. For example, with Microsoft Windows you can execute the “Print Screen” command by pressing [Ctrl] + [Print Screen] on the keyboard. The keyboard combination automatically copies the information displayed on your monitor to your clipboard, where it can then be pasted into Word, Excel, or PowerPoint. A second choice is Microsoft’s “Snipping Tool” program that enables you to select the desired area: “Free-form,” “Rectangular,” “Window” or “Full-Screen.” After your desired output area is selected, the image is automatically copied to your clipboard (the same as with the “Print Screen” command). Additionally, you have the ability to save the image file (as .png, .gif, .jpg, or .html) so that it may be used later. Finally, you can paste your image in the Paint option and select the part you want.

4All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

This is an example of This is an example of what you get when you what you get when you

use the SmartPLS use the SmartPLS Export to Image option.Export to Image option.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

5

Click here, select PLS Algorithm Click here, select PLS Algorithm to calculate model results.to calculate model results.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

6

This dialog box appears when This dialog box appears when you select the PLS Algorithm.you select the PLS Algorithm.

Missing values have not been Missing values have not been configured so you will have to configured so you will have to

Cancel this option and go to the Cancel this option and go to the datafile to set up.datafile to set up.

Default Settings to run PLS Algorithm – Click Finish to runDefault Settings to run PLS Algorithm – Click Finish to run

Trade-off in missing value Trade-off in missing value treatment:treatment:

Case wise replacement can Case wise replacement can greatly reduce the number of greatly reduce the number of

cases but sample mean cases but sample mean imputation reduces variance in imputation reduces variance in

your data.your data.

Preferred approach to deal Preferred approach to deal with missing data is combination with missing data is combination of sub-group mean and nearest of sub-group mean and nearest neighbor, or use EM imputation neighbor, or use EM imputation

using SPSS.using SPSS.

Always use path weighting schemeAlways use path weighting scheme

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

8

After double clicking on the datafile you get After double clicking on the datafile you get this screen. Check the box on the left to this screen. Check the box on the left to

indicate missing data in your datafile.indicate missing data in your datafile.Then change the Missing Value in the Then change the Missing Value in the

window to -99, as shown below. Finally, window to -99, as shown below. Finally, check the X beside the Full Data tab at top. check the X beside the Full Data tab at top.

That will close and save your changes That will close and save your changes

Double click on the datafile to get this screen. Double click on the datafile to get this screen.

After missing values have been After missing values have been reconfigured to -99.0reconfigured to -99.0

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

9

All other options are correct All other options are correct so check the Finish tab to so check the Finish tab to

run the modelrun the model..

When you select the PLS When you select the PLS Algorithm option this revised Algorithm option this revised dialog box appears. It now dialog box appears. It now shows the newly configured shows the newly configured

missing value option of -99.0.missing value option of -99.0.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

10

PLS Results for PLS Results for Simple ExampleSimple Example

Outer loadings, path Outer loadings, path coefficients, and Rcoefficients, and R22

shown on modelshown on model

PLS Results for PLS Results for Simple ExampleSimple Example

The structural model results enable us to determine, for example, that CUSA has the strongest effect on CUSL (0.504), followed by LIKE (0.342). COMP (0.009) has little effect on the dependent variable CUSL. The three exogenous constructs together explain 56.2% of the variance of the endogenous construct CUSL (R² = 0.562), as indicated by the value in the construct circle. COMP and LIKE also jointly explain 29.5% of the variance of CUSA.

12All rights reserved ©. Cannot be reproduced or distributed without express written permission from Sage, Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

Click here to obtain reports Click here to obtain reports that summarize model results.that summarize model results.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

13

This is an example of the reports that are available from SmartPLS. The type of information provided is shown in the menu on the left. For example, the Stop Criterion Changes is highlighted. Above the report shows the software took 4 iterations to obtain a solution.

Checking the Checking the algorithm stop algorithm stop

criterioncriterion

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

14

The above table of values is the The above table of values is the default report for the Path default report for the Path

Coefficients. To make this table Coefficients. To make this table easier to understand left click on easier to understand left click on the Toggle Zero Values button at the Toggle Zero Values button at

the top left. The results are shown the top left. The results are shown below.below.

To determine the To determine the statistical statistical

significance of the significance of the path coefficients, path coefficients, we must run the we must run the bootstrapping bootstrapping

option. To do so option. To do so click on the .splsm click on the .splsm file tab to return to file tab to return to

the SEM model the SEM model with the tool bar.with the tool bar.

Summary of PLS-SEM FindingsSummary of PLS-SEM Findings

1.1.The direct path from COMP to CUSA is 0.162 and The direct path from COMP to CUSA is 0.162 and

the direct path from COMP to CUSL is 0.009.the direct path from COMP to CUSL is 0.009.

2.2.The direct path from LIKE to CUSA is 0.424 and The direct path from LIKE to CUSA is 0.424 and

the direct path from LIKE to CUSL is 0.342.the direct path from LIKE to CUSL is 0.342.

3.3.The direct path from CUSA to CUSL is 0.504.The direct path from CUSA to CUSL is 0.504.

4.4.Overall, the model predicts 29.5% of the variance Overall, the model predicts 29.5% of the variance

in CUSA, and 56.2% of the variance in CUSL.in CUSA, and 56.2% of the variance in CUSL.

To determine significance levels, you must run Bootstrapping To determine significance levels, you must run Bootstrapping option. Look for under the calculate option.option. Look for under the calculate option.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

Click here, select Click here, select Bootstrapping option.Bootstrapping option.

Significance of PLS-SEM Parameters = BootstrappingSignificance of PLS-SEM Parameters = Bootstrapping

PLS-SEM does not assume the data is normally distributed, which PLS-SEM does not assume the data is normally distributed, which implies that parametric significance tests used in regression analyses implies that parametric significance tests used in regression analyses cannot be applied to test whether coefficients such as outer weights and cannot be applied to test whether coefficients such as outer weights and loadings are significant. Instead, PLS-SEM relies on a nonparametric loadings are significant. Instead, PLS-SEM relies on a nonparametric bootstrap procedure to test coefficients for their significance.bootstrap procedure to test coefficients for their significance.

In bootstrapping, a large number of subsamples (i.e., bootstrap In bootstrapping, a large number of subsamples (i.e., bootstrap samples) is drawn from the original sample – with replacement. samples) is drawn from the original sample – with replacement. Replacement means that each time an observation is drawn at random Replacement means that each time an observation is drawn at random from the sampling population, it is returned to the sampling population from the sampling population, it is returned to the sampling population before the next observation is drawn (i.e., the population from which the before the next observation is drawn (i.e., the population from which the observations are drawn always contains all the same elements). observations are drawn always contains all the same elements). Therefore, an observation for a certain subsample can be selected more Therefore, an observation for a certain subsample can be selected more than once, or may not be selected at all for another subsample. The than once, or may not be selected at all for another subsample. The number of bootstrap samples should be high but must be at least equal to number of bootstrap samples should be high but must be at least equal to the number of valid observations in the dataset. The recommended number the number of valid observations in the dataset. The recommended number of bootstrap samples is 5,000.of bootstrap samples is 5,000.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

18

When you get this dialog box make When you get this dialog box make sure you have chosen No Sign sure you have chosen No Sign

Changes, the number of cases is Changes, the number of cases is your sample size (344), and the your sample size (344), and the

number of samples is 5,000.number of samples is 5,000.

Then click the Finish tab to obtain Then click the Finish tab to obtain the results.the results.

If you have missing data do not use mean If you have missing data do not use mean replacement because bootstrapping draws replacement because bootstrapping draws samples with replacement. Use Casewise samples with replacement. Use Casewise Replacement.Replacement.

Use individual (sign) changes optionUse individual (sign) changes option

• Make sure the number of cases are Make sure the number of cases are equal to the number of equal to the number of validvalid observations in your dataset.observations in your dataset.

• Set Set casescases = samples size (or higher) = samples size (or higher)

Caution!!! Caution!!! It is a common mistake to set It is a common mistake to set samples equal to the overall number of samples equal to the overall number of observations.observations.

SmartPLS Bootstrapping SmartPLS Bootstrapping

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

20

The t values can be compared with the critical values from the standard normal

distribution to decide whether the coefficients are significantly different from zero. For example, the critical values for

significance levels of 1% (a = 0.01) and 5% (a = 0.05) probability of error are 2.57 and

1.96, respectively (two-tailed test) .One-tailed test for 5% (a = 0.05) level is .98.

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

21

By clicking on Report – Default Report you get a detailed overview of the bootstrapping results. The original estimate of the outer

weights is shown in the second column = Original Sample (0). If this number is divided by the Standard Deviation (STDEV) you get

the t value. For example, divide 0.5361 (0) by 0.0445 (STDEV) and you get 12.047 = the t statistic – shown below.

The t statistics in the table on The t statistics in the table on the right indicate that all the right indicate that all

measurement model measurement model loadings are statistically loadings are statistically

significant (> 0.05).significant (> 0.05).

All rights reserved ©. Cannot be reproduced or distributed without express written permission from Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.

22

The t statistics in the table below The t statistics in the table below indicate that four of the five indicate that four of the five

structural path coefficients are structural path coefficients are statistically significant (> 0.05).statistically significant (> 0.05).The only non-significant path is The only non-significant path is COMP – CUSL (t value = 0.1705).COMP – CUSL (t value = 0.1705).

Brief Instructions: Using SmartPLSBrief Instructions: Using SmartPLS

1.1. Load SmartPLS software – click onLoad SmartPLS software – click on

2.2. Create your new project – assign project name and data.Create your new project – assign project name and data.

3.3. Double-click to get Menu Bar.Double-click to get Menu Bar.

4.4. Draw model – see options below:Draw model – see options below:

• Insertion mode = Insertion mode =

• Selection mode = Selection mode =

• Connection mode = Connection mode =

5.5. Save model.Save model.

6.6. Click on calculate icon and select PLS algorithm on Click on calculate icon and select PLS algorithm on

the Pull-Down menu. Now accept the default options (or the Pull-Down menu. Now accept the default options (or

insert your own) by clicking Finish.insert your own) by clicking Finish.

24All rights reserved ©. Cannot be reproduced or distributed without express written permission from Sage, Prentice-Hall, McGraw-Hill, SmartPLS, and session presenters.