1<!DOCTYPE html> 2<html lang="en-us"> 3 <head> 4 <meta charset="utf-8"> 5 <meta name="viewport" content="width=device-width, initial-scale=1"> 6 <title>First-author papers | James Uanhoro</title> 7 <link rel="stylesheet" href="/css/style.css" /> 8 <link rel="stylesheet" href="/css/fonts.css" /> 9 10 </head> 11 12 <body> 13 <nav> 14 <ul class="menu"> 15 16 <li><a href="/">Home</a></li> 17 18 <li><a href="/papers/">First-author papers</a></li> 19 20 <li><a href="/post/">Blog posts</a></li> 21 22 <li><a href="/projects/">Programming projects</a></li> 23 24 <li><a href="/tags/">Tags</a></li> 25 26 <li><a href="/index.xml">Subscribe</a></li> 27 28 </ul> 29 <hr/> 30 </nav> 31 32 33 34<h1>First-author papers</h1> 35 36 37<p>These are publications I have some control over, so I’m able to share pre-publication PDFs and related resources.</p> 38<p>AERA papers I have no plans to submit these papers to journals are at the <a href="#american-educational-research-association-annual-meeting-papers">bottom of this page</a>.</p> 39<h2 id="in-press">In-Press</h2> 40<ul> 41<li>Uanhoro, J. O., & Rojo, M. (2026). A Hierarchical Ordinal Regression Model for Treatment-Reversal Designs with Application to Non-Overlap Effect Sizes. <em>Multivariate Behavioral Research, 0</em>(0), 1â28. <a href="https://doi.org/10.1080/00273171.2026.2619211">https://doi.org/10.1080/00273171.2026.2619211</a> 42<ul> 43<li><a href="/pdf/ssrhom_es_paper.pdf">Download PDF</a></li> 44<li><a href="https://osf.io/e5cwg/">Code and data – OSF</a></li> 45</ul> 46</li> 47<li>Uanhoro, J. O. (2025). Historical measurement information can be used to improve estimation of structural parameters in structural equation modelling with small samples. <em>Educational and Psychological Measurement</em>. <a href="https://doi.org/10.1177/00131644251330851">https://doi.org/10.1177/00131644251330851</a> 48<ul> 49<li><a href="/pdf/bcfa_eff.pdf">Download PDF</a></li> 50<li><a href="https://osf.io/rk45m/">Code and data – OSF</a></li> 51</ul> 52</li> 53</ul> 54<h2 id="2024">2024</h2> 55<ul> 56<li>Uanhoro, J. O. (2024). Bayesian structural equation models of correlation matrices. <em>Structural Equation Modeling: A Multidisciplinary Journal, 31</em>(4), 685–695. <a href="https://doi.org/10.1080/10705511.2024.2306532">https://doi.org/10.1080/10705511.2024.2306532</a> 57<ul> 58<li><a href="/pdf/corr_mat_sem_3.pdf">Download PDF</a></li> 59<li><a href="/pdf/corr_mat_sem_2_app.pdf">Online Appendix</a></li> 60<li><a href="https://osf.io/ex8gw/">Code and data – OSF</a></li> 61</ul> 62</li> 63<li>Uanhoro, J. O. (2024). Handling dependent samples in meta-analytic structural equation models: A Wishart-based approach. <em>Behavior Research Methods, 56</em>(6), 6101â6118. <a href="https://doi.org/10.3758/s13428-024-02340-4">https://doi.org/10.3758/s13428-024-02340-4</a> 64<ul> 65<li><a href="/pdf/meta_cfa_dep_3.pdf">Download PDF</a></li> 66<li><a href="https://osf.io/yd5q4/">Code and data – OSF</a></li> 67</ul> 68</li> 69<li>Uanhoro, J. O. (2024). Modeling Misspecification as a Parameter in Bayesian Structural Equation Models. <em>Educational and Psychological Measurement, 84</em>(2), 245–270. <a href="https://doi.org/10.1177/00131644231165306">https://doi.org/10.1177/00131644231165306</a> 70<ul> 71<li><a href="/pdf/bsem_fit_3.pdf">Download PDF</a></li> 72<li><a href="https://osf.io/29ydb/">Code and data – OSF</a></li> 73</ul> 74</li> 75</ul> 76<h2 id="2023">2023</h2> 77<ul> 78<li>Uanhoro, J. O. (2023). minorbsem: An R package for structural equation models that account for the influence of minor factors. <em>Journal of Open Source Software, 8</em>(86), 5292. <a href="https://doi.org/10.21105/joss.05292">https://doi.org/10.21105/joss.05292</a> 79<ul> 80<li>Free to read on JOSS</li> 81</ul> 82</li> 83<li>Uanhoro, J. O. (2023). Hierarchical Covariance Estimation Approach to Meta-Analytic Structural Equation Modeling. <em>Structural Equation Modeling: A Multidisciplinary Journal, 30</em>(4), 532–546. <a href="https://doi.org/10.1080/10705511.2022.2142128">https://doi.org/10.1080/10705511.2022.2142128</a> 84<ul> 85<li><a href="/pdf/m_sem_hier_cov_2.pdf">Download PDF</a></li> 86<li><a href="https://osf.io/rstzk/">Code and data – OSF</a></li> 87</ul> 88</li> 89<li>Uanhoro, J. O. (2023). Probability of superiority for comparing two groups of cluster
89s. <em>Behavior Research Methods, 55</em>(2), 646–656. <a href="https://doi.org/10.3758/s13428-022-01815-6">https://doi.org/10.3758/s13428-022-01815-6</a> 90<ul> 91<li><a href="/pdf/prob_sub_inf_02.pdf">Download PDF</a></li> 92<li><a href="https://osf.io/xd3ba/">Code and data – OSF</a></li> 93</ul> 94</li> 95</ul> 96<h2 id="2022">2022</h2> 97<ul> 98<li>Uanhoro, J. O., & Stone-Sabali, S. (2023). Beyond Group Mean Differences: A Demonstration With Scale Scores in Psychology. <em>Collabra: Psychology, 9</em>(1), 57610. <a href="https://doi.org/10.1525/collabra.57610">https://doi.org/10.1525/collabra.57610</a> 99<ul> 100<li>Free to read on Collabra</li> 101<li><a href="https://osf.io/r7qgc">Code and data – OSF</a></li> 102</ul> 103</li> 104</ul> 105<h2 id="2021">2021</h2> 106<ul> 107<li>Uanhoro, J. O., Wang, Y., & OâConnell, A. A. (2021). Problems with using odds ratios as effect sizes in binary logistic regression and alternative approaches. <em>Journal of Experimental Education, 89</em>(4), 670–689. <a href="https://doi.org/10.1080/00220973.2019.1693328">https://doi.org/10.1080/00220973.2019.1693328</a> 108<ul> 109<li><a href="/pdf/bin_eff_paper_revise_3.pdf">Download PDF</a></li> 110<li><a href="https://github.com/jamesuanhoro/reproducing_articles/tree/master/2019_jxe_odds_ratio">Code and data – GitHub</a></li> 111</ul> 112</li> 113</ul> 114<h2 id="american-educational-research-association-annual-meeting-papers">American Educational Research Association Annual Meeting papers</h2> 115<h3 id="2024-1">2024</h3> 116<ul> 117<li>Uanhoro, J. O. (2024). <em>A comparison of different prior choices for estimating the influence of minor factors in Bayesian structural equation models</em> [Paper Session]. 118<ul> 119<li><a href="/pdf/nrm_lss_lgt_gdp_aera.pdf">Download PDF</a></li> 120<li><a href="https://osf.io/xswy6/?view_only=4435656baf7740729054215f5bda64ba/">Code and data – OSF</a></li> 121</ul> 122</li> 123<li>Uanhoro, J. O. (2024). <em>Bayesian estimation of the RMSEA</em> [Paper Session]. 124<ul> 125<li><a href="/pdf/brmsea_aera.pdf">Download PDF</a></li> 126<li><a href="https://osf.io/dzxh7/?view_only=eb3cdf6c82fa4205a6b3ff40937ab687/">Code and data – OSF</a></li> 127</ul> 128</li> 129</ul> 130<h3 id="2022-1">2022</h3> 131<ul> 132<li>Uanhoro, J. O. (2022). <em>Modeling misspecification as a parameter in Bayesian structural equation models</em> [Paper Session]. 133<ul> 134<li><a href="/pdf/bsem_fit_aera_present.pdf">Presentation</a></li> 135</ul> 136</li> 137<li>Uanhoro, J. O. (2022). <em>Wishart hierarchical models for meta-analytic latent variable models: A demonstration with the Hospital Anxiety and Depression Scale</em> [Poster Session]. 138<ul> 139<li><a href="/pdf/m_wish_malvm.pdf">Download PDF</a></li> 140<li><a href="/pdf/AERA_Wishart_13.pdf">Poster</a></li> 141</ul> 142</li> 143</ul> 144<h3 id="2021-1">2021</h3> 145<ul> 146<li>Uanhoro, J. O., & Echeverria, S. A. (2021). <em>Multivariate count data analysis using a Bayesian hierarchical multinomial-t compound regression: A demonstration with collocations</em> [Paper Session]. 147<ul> 148<li><a href="/pdf/multinomial_compound.pdf">Presentation</a></li> 149</ul> 150</li> 151<li>Uanhoro, J. O. (2021). <em>A web-based application to support applied Bayesian data analysis</em> [Paper Session]. 152<ul> 153<li><a href="/pdf/es_calc.pdf">Download PDF</a></li> 154<li>Website: <a href="https://www.jamesuanhoro.com/project/bms/">https://www.jamesuanhoro.com/project/bms/</a></li> 155</ul> 156</li> 157</ul> 158<h3 id="2020-cancelled-conference">2020 (Cancelled conference)</h3> 159<ul> 160<li>Uanhoro, J. O. (2020). <em>
160Bayesian estimation of confirmatory factor analysis for count data with extensions for cross-classification</em> [Roundtable Session]. 161<ul> 162<li><a href="/pdf/cfa_count.pdf">Download PDF</a></li> 163</ul> 164</li> 165<li>Uanhoro, J. O. (2020). <em>Bayesian inference for the probability of superiority</em> [Roundtable Session]. 166<ul> 167<li><a href="/pdf/prob_sub_inf.pdf">Download PDF</a></li> 168<li>This paper assumes <em>t</em> distribution for data, it is more useful to assume the (continuous) data are ordinal as in the Beyond Group Mean Differences paper in Collabra above.</li> 169</ul> 170</li> 171</ul> 172<h3 id="2018">2018</h3> 173<ul> 174<li>Uanhoro, J. O., & OâConnell A. A. (2018). <em>A web-based application for effect sizes and their confidence intervals: standardized mean differences, binary outcomes, variance explained, and two-level multilevel models</em> [Paper Session]. 175<ul> 176<li><a href="/pdf/web_calc.pdf">Download PDF</a></li> 177</ul> 178</li> 179</ul> 180 181 182<ul> 183 184 185 186</ul> 187 188 <footer> 189
189<script defer src="//yihui.org/js/math-code.js"></script>
vendor: 1 bytes, line 189
189
190<script defer src="//mathjax.rstudio.com/latest/MathJax.js?config=TeX-MML-AM_CHTML"></script>
190 191
192<script defer src="//yihui.org/js/center-img.js"></script>
192 193 194 195 <hr/> 196 James Uanhoro | Powered by: <a href="https://www.netlify.com/">Netlify</a>, <a href="https://gohugo.io/">Hugo</a>, <a href="https://themes.gohugo.io/hugo-xmin/">Hugo XMin</a> 197 198 </footer> 199 </body> 200</html> 201
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.