R Codes for Dyadic Data Analysis 

A companion to ​

Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. York: Guilford Press.

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Chapter 1 Table 1.3

Converting data structures: Individual to Dyad, Dyad to Individual, and Individual to Pairwise 

Chapter 2 Table 2.1

Computing intra-class correlation with confidence interval for Table 2.1

Chapter 3

                 Table 3.1

Between dyads variable

        Table 3.3 -- example different from book

Within dyads variable

        Table 3.5 

Differencing between dyads 

Three ways to calculate ICC

Chapter 4 Table 4.3

Multi-level Modeling

Chapter 6

                Table 6.1    Equality of variances

                Table 6.2    Equality of correlations

                Table 6.3    Latent variable correlations

                Table 6.4    Omnibus test of distinguishability                                      Correlations pairwise method (p. 138)

Chapter 7

                Table 7.1    Mimic APIM with MLM results obtained with SPSS in Table 7.3

                Figure 7.2  Estimate indistinguishable APIM with SEM

                Figure 7.3  Estimate distinguishable APIM (with SEM)

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Chapter 8

                Table 8.4    Univariate SRM

                Table 8.9    Bivariate SRM

Chapter 11

                Table 11.4    Social network analysis

Chapter 10

                p. 292        Blog. One with many reciprocal design -- indistinguishable

                p. 292        One with many reciprocal design -- indistinguishable with MLM

                p. 293        One with many reciprocal design -- with SEM

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For R-based web applications, see Randi Garcia and Dave Kenny's Dyadic Data Analysis 2018 Workshop

Chapter 9

                Table 9.1    Family SRM