Conditional process modeling: Using structural equation modeling to examine contingent causal processes.
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doi.org/w75068391 →Countries where authors are citing Conditional process modeling: Using structural equation modeling to examine contingent causal processes.
This map shows the geographic impact of Conditional process modeling: Using structural equation modeling to examine contingent causal processes.. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Conditional process modeling: Using structural equation modeling to examine contingent causal processes. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Conditional process modeling: Using structural equation modeling to examine contingent causal processes. more than expected).
Fields of papers citing Conditional process modeling: Using structural equation modeling to examine contingent causal processes.
This network shows the impact of Conditional process modeling: Using structural equation modeling to examine contingent causal processes.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Conditional process modeling: Using structural equation modeling to examine contingent causal processes..
About Conditional process modeling: Using structural equation modeling to examine contingent causal processes.
This paper, published in 2013, received 331 indexed citations . Written by Andrew F. Hayes and Kristopher J. Preacher. It is primarily cited by scholars working on Clinical Psychology (97 citations), Sociology and Political Science (95 citations) and Social Psychology (88 citations).
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This paper is also available at doi.org/w75068391.