Dear colleagues> > in conducting a meta-analysis (of MRI data) I am running into the repeated issue: > > Error: Assigned data `single_study_df` must be compatible with existing data. ? Error occurred for column `accumbens_sd`. x Can't convert from <double> to <logical> due to loss of precision. * Locations: 1, 2. Run `rlang::last_error()` to see where the error occurred. > > This follows the commands > > for (region in regions){ > for (study in unique(df$studyid)){ > single_study_df <- df %>% filter(studyid==study) > if (is.na(single_study_df[sprintf('%s_mn', region)][[1]]) & !is.na(single_study_df[sprintf('%s_mn_l', region)])){ > df <- calc_bilat(study, region, r, df) > } > } > } > > > My colleague (cc'd) believed it may be an issue with tidyverse version, however using an older version (1.2.1), the issue persists. note 'accumbens' is the first of many columns so I suspect this is why it flags this up. > > I would greatly value your input on this matter > > Kind regards > > John Tully > > > >This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law. [[alternative HTML version deleted]]
On 06/09/2021 10:16 a.m., John Tully wrote:> Dear colleagues >> >> in conducting a meta-analysis (of MRI data) I am running into the repeated issue: >> >> Error: Assigned data `single_study_df` must be compatible with existing data. ? Error occurred for column `accumbens_sd`. x Can't convert from <double> to <logical> due to loss of precision. * Locations: 1, 2. Run `rlang::last_error()` to see where the error occurred.That certainly looks like a tidyverse error, specifically from the tibble package. Duncan Murdoch>> >> This follows the commands >> >> for (region in regions){ >> for (study in unique(df$studyid)){ >> single_study_df <- df %>% filter(studyid==study) >> if (is.na(single_study_df[sprintf('%s_mn', region)][[1]]) & !is.na(single_study_df[sprintf('%s_mn_l', region)])){ >> df <- calc_bilat(study, region, r, df) >> } >> } >> } >> >> >> My colleague (cc'd) believed it may be an issue with tidyverse version, however using an older version (1.2.1), the issue persists. note 'accumbens' is the first of many columns so I suspect this is why it flags this up. >> >> I would greatly value your input on this matter >> >> Kind regards >> >> John Tully >> >> >> >> > > > > > This message and any attachment are intended solely for the addressee > and may contain confidential information. If you have received this > message in error, please contact the sender and delete the email and > attachment. > > Any views or opinions expressed by the author of this email do not > necessarily reflect the views of the University of Nottingham. Email > communications with the University of Nottingham may be monitored > where permitted by law. > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
> Run `rlang::last_error()` to see where the error occurredWhat did rlang::last_error() show? -Bill On Mon, Sep 6, 2021 at 9:19 AM John Tully <John.Tully at nottingham.ac.uk> wrote:> Dear colleagues > > > > in conducting a meta-analysis (of MRI data) I am running into the > repeated issue: > > > > Error: Assigned data `single_study_df` must be compatible with existing > data. ? Error occurred for column `accumbens_sd`. x Can't convert from > <double> to <logical> due to loss of precision. * Locations: 1, 2. Run > `rlang::last_error()` to see where the error occurred. > > > > This follows the commands > > > > for (region in regions){ > > for (study in unique(df$studyid)){ > > single_study_df <- df %>% filter(studyid==study) > > if (is.na(single_study_df[sprintf('%s_mn', region)][[1]]) & !is.na(single_study_df[sprintf('%s_mn_l', > region)])){ > > df <- calc_bilat(study, region, r, df) > > } > > } > > } > > > > > > My colleague (cc'd) believed it may be an issue with tidyverse version, > however using an older version (1.2.1), the issue persists. note > 'accumbens' is the first of many columns so I suspect this is why it flags > this up. > > > > I would greatly value your input on this matter > > > > Kind regards > > > > John Tully > > > > > > > > > > > > > This message and any attachment are intended solely for the addressee > and may contain confidential information. If you have received this > message in error, please contact the sender and delete the email and > attachment. > > Any views or opinions expressed by the author of this email do not > necessarily reflect the views of the University of Nottingham. Email > communications with the University of Nottingham may be monitored > where permitted by law. > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]