w ISBN

.Rproj.user/FFFF18A2/bookdown-crossref/12-APPENDIX_Type1Error.Rmd.xref

@@ -1,5 +1,5 @@
 h1:appendices APPENDICES
-h1:type1 Type I Error
+h1:type-i-error Type I Error
 h2:type-i-error-defined Type I Error Defined
 h2:methods-for-managing-type-i-error Methods for Managing Type I Error
 h3:lsd-least-significant-difference-method LSD (Least Significant Difference) Method

.Rproj.user/FFFF18A2/bookdown-crossref/13-moReTwoWay.Rmd.xref

@@ -1,4 +1,4 @@
-h1:moRe Examples for Follow-up to Factorial ANOVA
+h1:examples-for-follow-up-to-factorial-anova Examples for Follow-up to Factorial ANOVA
 h2:research-vignette Research Vignette
 h3:quick-resimulating-of-the-data Quick Resimulating of the Data
 h2:analysis-of-simple-main-effects-with-orthogonal-contrasts Analysis of Simple Main Effects with Orthogonal Contrasts

.Rproj.user/FFFF18A2/bookdown-crossref/14-RMmultivariate.Rmd.xref

@@ -1,4 +1,4 @@
-h1:RMmultiv One-Way Repeated Measures with a Multivariate Approach
+h1:one-way-repeated-measures-with-a-multivariate-approach One-Way Repeated Measures with a Multivariate Approach
 h2:research-vignette Research Vignette
 h3:data-simulation Data Simulation
 h2:computing-the-omnibus-f Computing the Omnibus F

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-1-woRked_ReadySetR.Rmd.xref

@@ -1,8 +1,8 @@
 h2:homeworked-example Homeworked Example
-h3:perform-a-simple-mathematical-operation Perform a simple mathematical operation:
-h3:install-at-least-three-packages-we-will-commonly-use Install at least three packages we will commonly use:
-h3:copy-the-simulation-in-this-lesson-to-your-.rmd-file.-change-the-random-seed-and-run-the-simulation. Copy the simulation in this lesson to your .rmd file. Change the random seed and run the simulation.
-h3:save-the-resulting-data-as-a-.csv-or-.rds-file-in-the-same-file-as-you-saved-the-.rmd-file. Save the resulting data as a .csv or .rds file in the same file as you saved the .rmd file.
-h3:clear-your-environment-broom-in-upper-right. Clear your environment (broom in upper right).
-h3:run-the-describe-function-from-the-psych-package-with-your-simulated-data-that-you-imported-from-your-local-drive. Run the describe() function from the psych package with your simulated data that you imported from your local drive.
+h4:perform-a-simple-mathematical-operation Perform a simple mathematical operation:
+h4:install-at-least-three-packages-we-will-commonly-use Install at least three packages we will commonly use
+h4:copy-the-simulation-in-this-lesson-to-your-.rmd-file.-change-the-random-seed-and-run-the-simulation Copy the simulation in this lesson to your .rmd file. Change the random seed and run the simulation
+h4:save-the-resulting-data-as-a-.csv-or-.rds-file-in-the-same-file-as-you-saved-the-.rmd-file Save the resulting data as a .csv or .rds file in the same file as you saved the .rmd file
+h4:clear-your-environment-broom-in-upper-right Clear your environment (broom in upper right)
+h4:run-the-describe-function-from-the-psych-package-with-your-simulated-data-that-you-imported-from-your-local-drive Run the describe() function from the psych package with your simulated data that you imported from your local drive
 

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-10-woRked_ANCOVA.Rmd.xref

@@ -1,6 +1,6 @@
 h2:homeworked-example Homeworked Example
 h3:working-the-problem-with-r-and-r-packages Working the Problem with R and R Packages
-h4:narrate-the-research-vignette-describing-the-iv-dv-and-cov. Narrate the research vignette, describing the IV, DV, and COV.
+h4:narrate-the-research-vignette-describing-the-iv-dv-and-cov Narrate the research vignette, describing the IV, DV, and COV
 h4:simulate-or-import-and-format-data Simulate (or import) and format data
 h4:evaluate-statistical-assumptions Evaluate statistical assumptions
 h4:conduct-omnibus-anova-w-effect-size Conduct omnibus ANOVA (w effect size)

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-2-woRked_Preliminaries.Rmd.xref

@@ -7,13 +7,13 @@ h4:produce-splompairs.panels Produce SPLOM/pairs.panels
 h4:produce-an-apatables-matrix Produce an apaTables matrix
 h4:produce-an-apa-style-write-up-of-the-preliminary-analyses Produce an APA Style write-up of the preliminary analyses
 h3:hand-calculations Hand Calculations
-h4:create-a-variable-that-represents-the-mean. Create a variable that represents the mean.
-h4:create-a-variable-that-represents-the-mean-deviation. Create a variable that represents the mean deviation.
+h4:create-a-variable-that-represents-the-mean Create a variable that represents the mean
+h4:create-a-variable-that-represents-the-mean-deviation Create a variable that represents the mean deviation
 h4:what-is-the-value-of-the-sum-of-mean-deviations What is the value of the sum of mean deviations?
-h4:create-a-variable-that-represents-the-absolute-mean-deviation. Create a variable that represents the absolute mean deviation.
-h4:create-a-variable-that-represents-the-mean-deviation-squared. Create a variable that represents the mean deviation squared.
-h4:using-the-same-general-approach-calculate-the-mean-deviation-and-standard-deviation-for-a-second-continuously-scaled-variable. Using the same general approach, calculate the mean deviation and standard deviation for a second, continuously scaled variable.
+h4:create-a-variable-that-represents-the-absolute-mean-deviation Create a variable that represents the absolute mean deviation
+h4:create-a-variable-that-represents-the-mean-deviation-squared Create a variable that represents the mean deviation squared
+h4:using-the-same-general-approach-calculate-the-mean-deviation-and-standard-deviation-for-a-second-continuously-scaled-variable Using the same general approach, calculate the mean deviation and standard deviation for a second, continuously scaled variable
 h4:create-a-variable-that-represents-the-cross-product-of-the-mean-deviations.-what-is-the-sum-of-these-cross-products Create a variable that represents the  (of the mean deviations). What is the sum of these cross-products?
-h4:calculate-the-value-of-their-covariance. Calculate the value of their covariance.
-h4:calculate-value-of-correlation-coefficient. Calculate value of correlation coefficient.
+h4:calculate-the-value-of-their-covariance Calculate the value of their covariance
+h4:calculate-value-of-correlation-coefficient Calculate value of correlation coefficient
 

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-3-woRked_tOneSample.Rmd.xref

@@ -13,7 +13,7 @@ h4:using-the-steps-from-the-previous-lesson-hand-calculate-the-standard-deviatio
 h4:calculate-the-one-sample-t-test Calculate the one-sample -test
 h4:identify-the-degrees-of-freedom-associated-with-your-t-test Identify the degrees of freedom associated with your -test
 h4:locate-the-test-critical-value-for-your-test Locate the test critical value for your test
-h3:is-the-t-test-statistically-significant-why-or-why-not Is the -test statistically significant? Why or why not?
+h4:is-the-t-test-statistically-significant-why-or-why-not Is the -test statistically significant? Why or why not?
 h4:what-is-the-confidence-interval-around-your-sample-mean What is the confidence interval around your sample mean?
 h4:calculate-the-effect-size-i.e.-cohens-d-associated-with-your-t-test Calculate the effect size (i.e., Cohen’s  associated with your -test
 

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-5-woRked_tPaired.Rmd.xref

@@ -16,5 +16,5 @@ h4:locate-the-test-critical-value-for-your-paired-samples-t-test Locate the test
 h4:is-the-paired-samples-t-test-statistically-significant-why-or-why-not Is the paired samples -test statistically significant? Why or why not?
 h4:what-is-the-confidence-interval-around-the-mean-difference What is the confidence interval around the mean difference?
 h4:calculate-the-effect-size-i.e.-cohens-d-associated-with-your-paired-samples-t-test Calculate the effect size (i.e., Cohen’s  associated with your paired samples -test
-h4:assemble-the-results-into-a-statistical-string. Assemble the results into a statistical string.
+h4:assemble-the-results-into-a-statistical-string Assemble the results into a statistical string
 

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-6-woRked_OneWayANOVA.Rmd.xref

@@ -1,22 +1,22 @@
 h2:homeworked-example Homeworked Example
 h3:working-the-problem-with-r-and-r-packages Working the Problem with R and R Packages
-h4:narrate-the-research-vignette-describing-the-iv-and-dv.-the-data-you-analyze-should-have-at-least-3-levels-in-the-independent-variable-at-least-one-of-the-attempted-problems-should-have-a-significant-omnibus-test-so-that-follow-up-is-required. Narrate the research vignette, describing the IV and DV. The data you analyze should have at least 3 levels in the independent variable; at least one of the attempted problems should have a significant omnibus test so that follow-up is required).
-h4:simulate-or-import-and-format-data. Simulate (or import) and format data.
-h4:evaluate-statistical-assumptions. Evaluate statistical assumptions.
-h4:conduct-omnibus-anova-w-effect-size. Conduct omnibus ANOVA (w effect size).
-h4:conduct-one-set-of-follow-up-tests-narrate-your-choice. Conduct one set of follow-up tests; narrate your choice.
-h4:describe-approach-for-managing-type-i-error. Describe approach for managing Type I error.
-h4:apa-style-results-with-tables-and-figure. APA style results with table(s) and figure.
-h4:conduct-power-analyses-to-determine-the-power-of-the-current-study-and-a-recommended-sample-size. Conduct power analyses to determine the power of the current study and a recommended sample size.
+h4:narrate-the-research-vignette-describing-the-iv-and-dv.-the-data-you-analyze-should-have-at-least-3-levels-in-the-independent-variable-at-least-one-of-the-attempted-problems-should-have-a-significant-omnibus-test-so-that-follow-up-is-required Narrate the research vignette, describing the IV and DV. The data you analyze should have at least 3 levels in the independent variable; at least one of the attempted problems should have a significant omnibus test so that follow-up is required)
+h4:simulate-or-import-and-format-data Simulate (or import) and format data
+h4:evaluate-statistical-assumptions Evaluate statistical assumptions
+h4:conduct-omnibus-anova-w-effect-size Conduct omnibus ANOVA (w effect size)
+h4:conduct-one-set-of-follow-up-tests-narrate-your-choice Conduct one set of follow-up tests; narrate your choice
+h4:describe-approach-for-managing-type-i-error Describe approach for managing Type I error
+h4:apa-style-results-with-tables-and-figure APA style results with table(s) and figure
+h4:conduct-power-analyses-to-determine-the-power-of-the-current-study-and-a-recommended-sample-size Conduct power analyses to determine the power of the current study and a recommended sample size
 h3:hand-calculations Hand Calculations
-h4:using-traditional-nhst-null-hypothesis-testing-language-state-your-null-and-alternative-hypotheses. Using traditional NHST (null hypothesis testing language), state your null and alternative hypotheses.
-h4:calculate-sums-of-squares-total-sst.-steps-in-this-calculation-must-include-calculating-a-grand-mean-and-creating-variables-representing-the-mean-deviation-and-mean-deviation-squared. Calculate sums of squares total (SST). Steps in this calculation must include calculating a grand mean and creating variables representing the mean deviation and mean deviation squared.
-h4:calculate-the-sums-of-squares-for-the-model-ssm.-a-necessary-step-in-this-equation-is-to-calculate-group-means. Calculate the sums of squares for the model (SSM). A necessary step in this equation is to calculate group means.
-h4:calculate-the-sums-of-squares-residual-ssr.-a-necessary-step-in-this-equation-is-to-calculate-the-variance-for-each-group. Calculate the sums of squares residual (SSR). A necessary step in this equation is to calculate the variance for each group.
-h4:calculate-the-mean-square-model-mean-square-residual-and-f-test. Calculate the mean square model, mean square residual, and -test.
+h4:using-traditional-nhst-null-hypothesis-testing-language-state-your-null-and-alternative-hypotheses Using traditional NHST (null hypothesis testing language), state your null and alternative hypotheses
+h4:calculate-sums-of-squares-total-sst.-steps-in-this-calculation-must-include-calculating-a-grand-mean-and-creating-variables-representing-the-mean-deviation-and-mean-deviation-squared Calculate sums of squares total (SST). Steps in this calculation must include calculating a grand mean and creating variables representing the mean deviation and mean deviation squared
+h4:calculate-the-sums-of-squares-for-the-model-ssm.-a-necessary-step-in-this-equation-is-to-calculate-group-means Calculate the sums of squares for the model (SSM). A necessary step in this equation is to calculate group means
+h4:calculate-the-sums-of-squares-residual-ssr.-a-necessary-step-in-this-equation-is-to-calculate-the-variance-for-each-group Calculate the sums of squares residual (SSR). A necessary step in this equation is to calculate the variance for each group
+h4:calculate-the-mean-square-model-mean-square-residual-and-f-test Calculate the mean square model, mean square residual, and -test
 h4:what-are-the-degrees-of-freedom-for-your-numerator-and-denominator What are the degrees of freedom for your numerator and denominator?
-h4:locate-the-test-critical-value-for-your-one-way-anova. Locate the test critical value for your one-way ANOVA.
+h4:locate-the-test-critical-value-for-your-one-way-anova Locate the test critical value for your one-way ANOVA
 h4:is-the-f-test-statistically-significant-why-or-why-not Is the -test statistically significant? Why or why not?
 h4:calculate-and-interpret-the-eta2-effect-size Calculate and interpret the  effect size
-h4:assemble-the-results-into-a-statistical-string. Assemble the results into a statistical string.
+h4:assemble-the-results-into-a-statistical-string Assemble the results into a statistical string
 

.Rproj.user/FFFF18A2/bookdown-crossref/Worked_Examples/15-7-woRked_Factorial.Rmd.xref

@@ -1,20 +1,20 @@
 h2:homeworked-example Homeworked Example
 h3:working-the-problem-with-r-and-r-packages Working the Problem with R and R Packages
-h4:narrate-the-research-vignette-describing-the-iv-and-dv.-miniminally-the-data-should-allow-the-analysis-of-a-2-x-3-or-3-x-2-design.-at-least-one-of-the-problems-you-work-should-have-a-significant-interaction-effect-so-that-follow-up-is-required. Narrate the research vignette, describing the IV and DV. Miniminally, the data should allow the analysis of a 2 x 3 (or 3 X 2) design. At least one of the problems you work should have a significant interaction effect so that follow-up is required.
-h4:simulate-or-import-and-format-data. Simulate (or import) and format data.
-h4:evaluate-statistical-assumptions. Evaluate statistical assumptions.
-h4:conduct-omnibus-anova-w-effect-size. Conduct omnibus ANOVA (w effect size).
-h4:conduct-one-set-of-follow-up-tests-narrate-your-choice. Conduct one set of follow-up tests; narrate your choice.
-h4:describe-approach-for-managing-type-i-error. Describe approach for managing Type I error.
-h4:apa-style-results-with-tables-and-figure. APA style results with table(s) and figure.
-h4:conduct-power-analyses-to-determine-the-power-of-the-current-study-and-a-recommended-sample-size. Conduct power analyses to determine the power of the current study and a recommended sample size.
+h4:narrate-the-research-vignette-describing-the-iv-and-dv.-miniminally-the-data-should-allow-the-analysis-of-a-2-x-3-or-3-x-2-design.-at-least-one-of-the-problems-you-work-should-have-a-significant-interaction-effect-so-that-follow-up-is-required Narrate the research vignette, describing the IV and DV. Miniminally, the data should allow the analysis of a 2 x 3 (or 3 X 2) design. At least one of the problems you work should have a significant interaction effect so that follow-up is required
+h4:simulate-or-import-and-format-data Simulate (or import) and format data
+h4:evaluate-statistical-assumptions Evaluate statistical assumptions
+h4:conduct-omnibus-anova-w-effect-size Conduct omnibus ANOVA (w effect size)
+h4:conduct-one-set-of-follow-up-tests-narrate-your-choice Conduct one set of follow-up tests; narrate your choice
+h4:describe-approach-for-managing-type-i-error Describe approach for managing Type I error
+h4:apa-style-results-with-tables-and-figure APA style results with table(s) and figure
+h4:conduct-power-analyses-to-determine-the-power-of-the-current-study-and-a-recommended-sample-size Conduct power analyses to determine the power of the current study and a recommended sample size
 h3:hand-calculations Hand Calculations
-h4:calculate-sums-of-squares-total-sst-for-the-omnibus-anova.-steps-in-this-calculation-must-include-calculating-a-grand-mean-and-creating-variables-representing-the-mean-deviation-and-mean-deviation-squared. Calculate sums of squares total (SST) for the omnibus ANOVA. Steps in this calculation must include calculating a grand mean and creating variables representing the mean deviation and mean deviation squared.
-h4:calculate-the-sums-of-squares-for-the-model-ssm-for-the-omnibus-anova.-a-necessary-step-in-this-equation-is-to-calculate-group-means-for-all-combinations-of-the-levels-in-the-factorial-design. Calculate the sums of squares for the model (SSM) for the omnibus ANOVA. A necessary step in this equation is to calculate group means for all combinations of the levels in the factorial design.
-h4:calculate-the-sums-of-squares-residual-ssr-for-the-omnibus-anova.-a-necessary-step-in-this-equation-is-to-calculate-the-variance-for-each-group. Calculate the sums of squares residual (SSR) for the omnibus ANOVA. A necessary step in this equation is to calculate the variance for each group.
-h4:calculate-sums-of-squares-model-ssm-for-each-of-the-factors-in-the-model. Calculate sums of squares model (SSM) for each of the factors in the model.
-h4:create-a-source-table-that-includes-the-sums-of-squares-degrees-of-freedom-mean-squares-f-values-and-f-critical-values. Create a source table that includes the sums of squares, degrees of freedom, mean squares,  values, and  critical values.
+h4:calculate-sums-of-squares-total-sst-for-the-omnibus-anova.-steps-in-this-calculation-must-include-calculating-a-grand-mean-and-creating-variables-representing-the-mean-deviation-and-mean-deviation-squared Calculate sums of squares total (SST) for the omnibus ANOVA. Steps in this calculation must include calculating a grand mean and creating variables representing the mean deviation and mean deviation squared
+h4:calculate-the-sums-of-squares-for-the-model-ssm-for-the-omnibus-anova.-a-necessary-step-in-this-equation-is-to-calculate-group-means-for-all-combinations-of-the-levels-in-the-factorial-design Calculate the sums of squares for the model (SSM) for the omnibus ANOVA. A necessary step in this equation is to calculate group means for all combinations of the levels in the factorial design
+h4:calculate-the-sums-of-squares-residual-ssr-for-the-omnibus-anova.-a-necessary-step-in-this-equation-is-to-calculate-the-variance-for-each-group Calculate the sums of squares residual (SSR) for the omnibus ANOVA. A necessary step in this equation is to calculate the variance for each group
+h4:calculate-sums-of-squares-model-ssm-for-each-of-the-factors-in-the-model Calculate sums of squares model (SSM) for each of the factors in the model
+h4:create-a-source-table-that-includes-the-sums-of-squares-degrees-of-freedom-mean-squares-f-values-and-f-critical-values Create a source table that includes the sums of squares, degrees of freedom, mean squares,  values, and  critical values
 h4:are-the-f-tests-for-the-main-and-interaction-effects-statistically-significant-why-or-why-not Are the -tests for the main and interaction effects statistically significant? Why or why not?
-h4:calculate-and-interpret-the-eta2-effect-sizes-for-the-main-and-interaction-effects. Calculate and interpret the  effect sizes for the main and interaction effects.
-h4:assemble-the-results-into-their-statistical-strings. Assemble the results into their statistical strings.
+h4:calculate-and-interpret-the-eta2-effect-sizes-for-the-main-and-interaction-effects Calculate and interpret the  effect sizes for the main and interaction effects
+h4:assemble-the-results-into-their-statistical-strings Assemble the results into their statistical strings