Open-source software improves the reproducibility of scientific research. Because existing open-source tools often do not offer dedicated support for longitudinal data collection on phones and computers, we built formr, a study framework that enables researchers to conduct both simple surveys and more intricate studies. With automated email and text message reminders that can be sent according to any schedule, longitudinal and experience-sampling studies become easy to implement. By integrating a web-based application programming interface for the statistical programming language R via OpenCPU, formr allows researchers to use a familiar programming language to enable complex features. These can range from adaptive testing, to graphical and interactive feedback, to integration with non-survey data sources such as self-trackers or online social network data. Here we showcase three studies created in formr: a study of couples with dyadic feedback; a longitudinal study over months, which included social networks and peer and partner ratings; and a diary study with daily invitations sent out by text message and email and extensive feedback on intraindividual patterns.
Open source software improves the reproducibility of scientific research. Because existing open source tools often do not offer dedicated support for longitudinal data collection on phones and computers, we built formr, a study framework that enables researchers to conduct both simple surveys and more intricate studies. With automated email and text message reminders according to any schedule, longitudinal and experience sampling studies become easy to implement. By integrating a web-based API for the statistical programming language R via OpenCPU, formr allows researchers to use a familiar programming language to enable complex features. These can range from adaptive testing to graphical and interactive feedback, to integration with non-survey data sources such as self-trackers or online social network data. Here, we showcase three studies created in formr: a study of couples with dyadic feedback; a longitudinal study over months including social networks, peer, and partner ratings; and a diary study with daily invitations by text message and email and extensive feedback on intraindividual patterns.
Event history calendars (EHCs) are popular tools for retrospective data collection. Originally conceptualized as face‐to‐face interviews, EHCs contain various questions about the respondents' autobiography in order to use their experiences as cues to facilitate remembering. For relationship researchers, EHCs are particularly valuable when trying to reconstruct the relational past of individuals. However, although many studies are conducted online nowadays, no freely available online adaptation of the EHC is available yet. In this tutorial, detailed instructions are provided on how to implement an online EHC for the reconstruction of romantic relationship histories within the open‐source framework formr. Ways to customize the online EHC and provide a template for researchers to adapt the tool for their own purposes are showcased.
Event history calendars (EHCs) are popular tools for retrospective data collection. Originally conceptualized as face-to-face interviews, EHCs contain various questions about the respondents’ autobiography in order to use their experiences as cues to facilitate remembering. For relationship researchers, EHCs are particularly valuable when trying to reconstruct the relational past of individuals. However, while many studies are conducted online nowadays, no freely available online adaptation of the EHC is available yet. In this tutorial, we provide detailed instructions on how to implement an online EHC for the reconstruction of romantic relationship histories within the open source framework formr. We showcase on ways to customize the online EHC and provide a template for researchers to adapt the tool for their own purposes.
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