cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3520004
title: Supplementary Data - Nanopore cDNA With and Without mtDNA

description: Update (v1.5.2-Demo): added 60Mb demonstration dataset for teaching / learning purposes (<em>reads_SampleDESet_sampled_60k.fastq.gz</em>). This dataset can be used for testing demultiplexing, or carrying out differential expression analysis on nanopore reads. There are 15k reads sampled from each run (subset on ~300 genes), plus 7.5k chimeric reads from the Dec17 run, plus 7.5k reads sampled from from CG009/BC08. The gene subset includes ~100 genes differentially-expressed between 4T1WT and 4T1ρ<sup>0</sup> cell lines, plus an additional ~200 genes with minimal differential expression observed between any 4T1 cell lines (i.e. a housekeeping gene set): BC01, BC02, BC04, BC06 - 4T1 cell line reads from three sequencing runs (005, 005, 004, Dec17) BC03, BC05, BC07 - 4T1ρ<sup>0</sup> (without mtDNA) cell line reads from three sequencing runs (005, 004, Dec17) BC08 - 4T1ρ<sup>0</sup>SC (from subcutaneous tumour) cell line reads from one sequencing run (009) [note: v1.5.1-Demo has the wrong sequence ID for BC08 reads] Update (v1.5.0-Called): added full 4T1 call set (called using guppy high-accuracy v3.2.2), gene transcript count tables, and differential expression results Update (v1.4.1-Chimeric): added more example called chimeric reads of various [unclassified] categories Update (v1.4.0-Chimeric): added example chimeric reads, one formed [presumably] during sample prep ["conjugation"], another formed in-silico ["double read"] Update (v1.3.0-DESeq2): added count table and metadata file for DESeq2 analysis Update (v1.2.1-10k): added 10k of FASTQ reads from a more recent run (part of the same differential expression project). Supplementary data to go with David Eccles' poster about nanopore cDNA sequencing with and without mitochondrial DNA. Reference mouse mtDNA and mtDNA reads from 4T1 cells (from MinION cDNA sequencing, and from SRA run SRR6747859). fwd_4T1_BC06.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from Wildtype 4T1 strain, filtered as transcript-forward orientation rev_4T1_BC06.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from Wildtype 4T1 strain, filtered as transcript-reverse orientation fwd_4T1_BC07.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from 4T1ρ0 strain (no mitochondrial DNA), filtered as transcript-forward orientation rev_4T1_BC07.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from 4T1ρ0 strain (no mitochondrial DNA), filtered as transcript-reverse orientation Other intermediate data files are also included, see `4way_mapping_process.txt` for more details. The mpileup differential coverage script can be found here.
DOI: 10.7910/dvn/hjsqnl/5wirou
title: Study1_NL17_coding.R

description: Netherlands 2017 coding data
DOI: 10.7910/dvn/hjsqnl/7p0ewl
title: Study1_Germany_coding.R

description: Germany coding data
DOI: 10.7910/dvn/hjsqnl/dtagrj
title: Study1_NL14_coding.R

description: Netherlands 2014 coding data
DOI: 10.7910/dvn/hjsqnl/kgbzxt
title: Study1_Denmark_coding.R

description: Denmark coding data
DOI: 10.7910/dvn/hjsqnl/oaiezo
title: 1. ReadMe.pdf

description: Read this file first: instructions how to set up replication
DOI: 10.7910/dvn/hjsqnl/q9lw3g
title: 2. Data Access

description: Document explaining how to access datasets that could not be deposited on Dataverse
DOI: 10.7910/dvn/hjsqnl/wkcfki
title: Study1_NL12_coding.R

description: Netherlands 2012 coding data
DOI: 10.7910/dvn/hjsqnl/x7pqit
title: 4. Functions.R

description: Functions needed to replicate results
DOI: 10.7910/dvn/hjsqnl/gqzssm
title: Study1_Swiss_Election15_coding.R

description: Swiss elections coding data
DOI: 10.7910/dvn/hjsqnl/kyhmf2
title: Study1_Spain_coding.R

description: Spain coding data
DOI: 10.7910/dvn/hjsqnl/lanuuc
title: Study1_Swiss_Household15_coding.R

description: Swiss househould 15 coding data
DOI: 10.7910/dvn/hjsqnl/nqcaeu
title: Study1_UK_BritishElectionStudies_recreate_data.R

description: British Election recreate analysis data
DOI: 10.7910/dvn/hjsqnl/oiapda
title: Study1_Swiss_Household09_coding.R

description: Swiss househould 09 coding data
DOI: 10.7910/dvn/hjsqnl/updcxx
title: Study1_UK_BritishElectionStudies_coding.R

description: British Election coding dadta
DOI: 10.7910/dvn/hjsqnl/4n4o0b
title: Study1_Appendix_A19.R

description: Study 1 Appendix A19
DOI: 10.7910/dvn/hjsqnl/7qgeou
title: Study1_US_ANES_coding.R

description: US ANES coding data
DOI: 10.7910/dvn/hjsqnl/al78uo
title: Study1_Denmark_results.R

description: Denmark results
DOI: 10.7910/dvn/hjsqnl/cyhcwi
title: Study1_US_ANES_recreate_data.R

description: US ANES recreate analysis data
DOI: 10.7910/dvn/hjsqnl/j15uir
title: Study1_Figure1.R

description: Code to create Figure 1
DOI: 10.7910/dvn/hjsqnl/ofpmps
title: Study1_Venezuela_coding.R

description: Venezuela coding data
DOI: 10.7910/dvn/hjsqnl/p0nbwv
title: Study1_Figure1_lrideology.R

description: Study 1 Appendix A17 no ideology
DOI: 10.7910/dvn/hjsqnl/wqqsnw
title: Study1_UK_UnderstandingSociety_coding.R

description: UK Understanding Society coding data
DOI: 10.7910/dvn/hjsqnl/xd49ix
title: Study1_Appendix_A18.R

description: Study 1 Appendix A18
DOI: 10.5281/zenodo.3519930
title: Supplementary Data - Nanopore cDNA With and Without mtDNA

description: Update (v1.5.1-Demo): added 60Mb demonstration dataset for teaching / learning purposes. This dataset can be used for testing demultiplexing, or carrying out differential expression analysis on nanopore reads. There are 15k reads sampled from each run (subset on ~300 genes), plus 7.5k chimeric reads from the Dec17 run, plus 7.5k reads sampled from from CG009/BC08. The gene subset includes ~100 genes differentially-expressed between 4T1WT and 4T1ρ<sup>0</sup> cell lines, plus an additional ~200 genes with minimal differential expression observed between any 4T1 cell lines (i.e. a housekeeping gene set): BC01, BC02, BC04, BC06 - 4T1 cell line reads from three sequencing runs (005, 005, 004, Dec17) BC03, BC05, BC07 - 4T1ρ<sup>0</sup> (without mtDNA) cell line reads from three sequencing runs (005, 004, Dec17) BC08 - 4T1ρ<sup>0</sup>SC (from subcutaneous tumour) cell line reads from one sequencing run (009) Update (v1.5.0-Called): added full 4T1 call set (called using guppy high-accuracy v3.2.2), gene transcript count tables, and differential expression results Update (v1.4.1-Chimeric): added more example called chimeric reads of various [unclassified] categories Update (v1.4.0-Chimeric): added example chimeric reads, one formed [presumably] during sample prep ["conjugation"], another formed in-silico ["double read"] Update (v1.3.0-DESeq2): added count table and metadata file for DESeq2 analysis Update (v1.2.1-10k): added 10k of FASTQ reads from a more recent run (part of the same differential expression project). Supplementary data to go with David Eccles' poster about nanopore cDNA sequencing with and without mitochondrial DNA. Reference mouse mtDNA and mtDNA reads from 4T1 cells (from MinION cDNA sequencing, and from SRA run SRR6747859). fwd_4T1_BC06.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from Wildtype 4T1 strain, filtered as transcript-forward orientation rev_4T1_BC06.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from Wildtype 4T1 strain, filtered as transcript-reverse orientation fwd_4T1_BC07.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from 4T1ρ0 strain (no mitochondrial DNA), filtered as transcript-forward orientation rev_4T1_BC07.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from 4T1ρ0 strain (no mitochondrial DNA), filtered as transcript-reverse orientation Other intermediate data files are also included, see `4way_mapping_process.txt` for more details. The mpileup differential coverage script can be found here.
DOI: 10.7910/dvn/hjsqnl/axlzp8
title: Study1_SSI_Appendix_A16.R

description: Study 1 Appendix A16
DOI: 10.7910/dvn/hjsqnl/cdrnbh
title: Study1_NL12_results.R

description: Netherlands 2012 results
DOI: 10.7910/dvn/hjsqnl/hzsmjk
title: Study1_meta.R

description: Study 1 pooled analyses
DOI: 10.7910/dvn/hjsqnl/l6mdem
title: Study1_Figure1_no_cynicism.R

description: Study 1 Appendix A17 no cynicism
DOI: 10.7910/dvn/hjsqnl/r9lujf
title: Study1_NL17_results.R

description: Netherlands 2017 results
DOI: 10.7910/dvn/hjsqnl/slkjji
title: Study1_Spain_results.R

description: Spain results
DOI: 10.7910/dvn/hjsqnl/szgycx
title: Study1_Germany_results.R

description: Germany results
DOI: 10.7910/dvn/hjsqnl/uoa1qp
title: Study1_NL14_results.R

description: Netherlands 2014 results
DOI: 10.7910/dvn/hjsqnl/uvny9i
title: Study1_SSI_Appendix_A.15.R

description: Study 1 Appendix A15
DOI: 10.7910/dvn/hjsqnl/amxnte
title: Study1_Swiss_Household15_results.R

description: Swiss household 15 results
DOI: 10.7910/dvn/hjsqnl/dv49sx
title: Study1_US_ANES_results.R

description: ANES results
DOI: 10.7910/dvn/hjsqnl/e5rbsj
title: Study1_UK_BritishElectionStudies_results.R

description: British Election results
DOI: 10.7910/dvn/hjsqnl/rsfso3
title: Study1_Swiss_Household09_results.R

description: Swiss household 09 results
DOI: 10.7910/dvn/hjsqnl/uqv4r2
title: Study1_dataverse_Denmark.RData

description: Study 1: Danish data
DOI: 10.7910/dvn/hjsqnl/wearcg
title: Study1_Swiss_Election15_results.R

description: Swiss election results
DOI: 10.7910/dvn/hjsqnl/xks4hj
title: Study1_UK_UnderstandingSociety_results.R

description: UK Undertanding Society results
DOI: 10.7910/dvn/hjsqnl/xqyysn
title: Study1_Venezuela_results.R

description: Venezuela results
DOI: 10.25919/5db4ef467e0c0
title: Parkes observations for project P958 semester 2019OCTS_09

description: Fast radio bursts (FRBs) continue to raise more questions than they answer. Until last year, only one burst – the only one known to repeat - had been localized to a bright radio nebula (either a young supernova remnant or pulsar wind nebulae) in a distant dwarf galaxy. Over the last two year searches with the Australian Square Kilometre Array Pathfinder (ASKAP) have detected 31 bursts, five of which have been localised to host galaxies at redshifts ranging from 0.1 to 0.5. These bursts and their hosts are very unlike the repeater, suggesting there may be a dichotomy in the population. However one of the arcminute-localised ASKAP FRBs has recently been found to repeat. Here we propose to search and study repetitions in this FRB population. Our comprehensive sample and a dense monitoring campaign of well localised bursts, at a fluence limit more than 60 times lower than that of their detections to characterise the fraction of bursts that repeat. For bursts that repeat the unique wide bandwidth observations will be used to test leading models of burst emission.
DOI: 10.7910/dvn/hjsqnl/a1yzgs
title: Study2_data.csv

description: Study 2 dataset
DOI: 10.7910/dvn/hjsqnl/b30tfr
title: Study1_US_ANES_analysisdata.tab

description: Study 1: ANES analysis dataset
DOI: 10.7910/dvn/hjsqnl/copb3e
title: Study2_Appendix_B10.R

description: Study 2 Appendix B10
DOI: 10.7910/dvn/hjsqnl/ct2jtb
title: Study2_Analyses.R

description: Study 2 analyses
DOI: 10.7910/dvn/hjsqnl/fu8e9i
title: Study2_coding.R

description: Study 2 coding data
DOI: 10.7910/dvn/hjsqnl/ybafe3
title: Study1_dataverse_Netherlands2014.RData

description: Study 1: Netherlands 2014 data
DOI: 10.7910/dvn/hjsqnl/zvfwy0
title: Study1_UK_BES_analysisdata.Rdata

description: Study 1: British Election Studies analysis dataset
DOI: 10.5281/zenodo.3519933
title: Bomb calorimetry: Gross energy and behavioural analysis

description: 1)In semio-chemical research, the production of glandular scent-secretions is generally considered energetically costly. Measuring these costs, however, has hitherto been difficult. Whereas most glandular secretions contain volatile organic compounds (VOCs), non-volatile organic compounds (non-VOCs), and proteins, current analytical techniques are time-consuming, and specific to one or two chemical component classes, necessitating several analyses to be run in parallel. In addition, most techniques measure relative rather than absolute compound amounts, thus requiring further data processing. Bomb calorimetry bypasses these limitations by oxidising all chemical bonds within a sample simultaneously. Our proof-of-concept study shows that bomb calorimetry can quantify the energetic content (‘Calorific Value’: CV) of freeze-dried subcaudal gland secretions (CV<sub>dry</sub>), which European badgers (<em>Meles meles</em>) use for fitness advertisement. From this measure, it is possible to calculate additional biologically-meaningful metrics: The calorific value of natural (non-dried) secretion (CV<sub>natural</sub>), energy content of individual scent-marks (CV<sub>scentmark</sub>), and the (minimum) energy an individual allocates to scent production (CV<sub>pouch</sub>). Female CV<sub>dry</sub>, CV<sub>natural</sub> and CV<sub>scentmark</sub> were highest in autumn, while equivalent male values showed no significant variation. In contrast, male – but not female - CV<sub>pouch</sub> was significantly higher in spring than in other seasons. Sexual maturity had a significant impact on female - but not male - CV<sub>natural </sub>with sexually mature females having higher CV<sub>natural</sub> than immature females. These results accord with scent-marking behaviour where males increase marking activity to advertise, while females vary olfactory information content. Here, our biological validation with scent-provisioning experiments evidenced that badgers can detect these differences in calorific value of secretions and modify their response behaviour accordingly. We conclude that bomb calorimetry provides a valuable tool for semio-chemical research, although the biological interpretation of results must take additional measures to CV<sub>dry</sub> into account to be comprehensive.
DOI: 10.5281/zenodo.3519934
title: Bomb calorimetry: Gross energy and behavioural analysis

description: 1)In semio-chemical research, the production of glandular scent-secretions is generally considered energetically costly. Measuring these costs, however, has hitherto been difficult. Whereas most glandular secretions contain volatile organic compounds (VOCs), non-volatile organic compounds (non-VOCs), and proteins, current analytical techniques are time-consuming, and specific to one or two chemical component classes, necessitating several analyses to be run in parallel. In addition, most techniques measure relative rather than absolute compound amounts, thus requiring further data processing. Bomb calorimetry bypasses these limitations by oxidising all chemical bonds within a sample simultaneously. Our proof-of-concept study shows that bomb calorimetry can quantify the energetic content (‘Calorific Value’: CV) of freeze-dried subcaudal gland secretions (CV<sub>dry</sub>), which European badgers (<em>Meles meles</em>) use for fitness advertisement. From this measure, it is possible to calculate additional biologically-meaningful metrics: The calorific value of natural (non-dried) secretion (CV<sub>natural</sub>), energy content of individual scent-marks (CV<sub>scentmark</sub>), and the (minimum) energy an individual allocates to scent production (CV<sub>pouch</sub>). Female CV<sub>dry</sub>, CV<sub>natural</sub> and CV<sub>scentmark</sub> were highest in autumn, while equivalent male values showed no significant variation. In contrast, male – but not female - CV<sub>pouch</sub> was significantly higher in spring than in other seasons. Sexual maturity had a significant impact on female - but not male - CV<sub>natural </sub>with sexually mature females having higher CV<sub>natural</sub> than immature females. These results accord with scent-marking behaviour where males increase marking activity to advertise, while females vary olfactory information content. Here, our biological validation with scent-provisioning experiments evidenced that badgers can detect these differences in calorific value of secretions and modify their response behaviour accordingly. We conclude that bomb calorimetry provides a valuable tool for semio-chemical research, although the biological interpretation of results must take additional measures to CV<sub>dry</sub> into account to be comprehensive.
DOI: 10.7910/dvn/niwsmi/q0f3wy
title: RebelLeader_sawyerbondcunningham.tab

description: :unav
DOI: 10.7910/dvn/niwsmi/qsjvbk
title: sawyerbondcunningham_do_file.do

description: :unav
DOI: 10.7910/dvn/ncuspz/4bciky
title: Table B1 Column 1.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/8jeoei
title: Replication_Figures.R

description: :unav
DOI: 10.7910/dvn/ncuspz/jgomni
title: merged_replication_data.tab

description: :unav
DOI: 10.7910/dvn/ncuspz/pt08wk
title: Table B7 Data.dat

description: :unav
DOI: 10.7910/dvn/ncuspz/puutx9
title: Nelson_Tucker_Replication_Readme.docx

description: :unav
DOI: 10.7910/dvn/ncuspz/sqxcus
title: replication_nelson_tucker_jop.do

description: :unav
DOI: 10.7910/dvn/ncuspz/2wncnk
title: Table B6.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/6c6n2z
title: Table B1 Column 2.out

description: :unav
DOI: 10.7910/dvn/ncuspz/9ojdmn
title: Table B1 Data.dat

description: :unav
DOI: 10.7910/dvn/ncuspz/blhdqk
title: Table B7.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/ioetuz
title: Table B3 Column 2.out

description: :unav
DOI: 10.7910/dvn/ncuspz/k3xphf
title: Table B2 Column 1.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/njqjzu
title: Table B1 Column 1.out

description: :unav
DOI: 10.7910/dvn/ncuspz/urmbwx
title: Table B6 Data.dat

description: :unav
DOI: 10.7910/dvn/ncuspz/wosvju
title: Table B1 Column 2.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/88gdqe
title: Table B2 Column 2.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/bnqgxy
title: Table B4.out

description: :unav
DOI: 10.7910/dvn/ncuspz/ddfley
title: Table B5.out

description: :unav
DOI: 10.7910/dvn/ncuspz/gqvmxd
title: Table B5.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/hw0c4i
title: Table B3 Column 1.out

description: :unav
DOI: 10.7910/dvn/ncuspz/iafqd4
title: Table B2 Column 2.out

description: :unav
DOI: 10.7910/dvn/ncuspz/ik1ln6
title: Table B4.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/npa7rm
title: Table B3 Column 1.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/5ey39o
title: Table A1 Column 1.out

description: :unav
DOI: 10.7910/dvn/ncuspz/5k3mi8
title: Table B2 Column 1.out

description: :unav
DOI: 10.7910/dvn/ncuspz/a2bvcx
title: Table A1 Column 2.out

description: :unav
DOI: 10.7910/dvn/ncuspz/eaukqf
title: Table B6.out

description: :unav
DOI: 10.7910/dvn/ncuspz/iofd1l
title: Table A1 Column 2.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/jev17x
title: Table A2.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/v5nqh7
title: Table B3 Column 2.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/we7qjd
title: Table B7.out

description: :unav
DOI: 10.7910/dvn/ncuspz/wpsndk
title: Table B3.dat

description: :unav
DOI: 10.7910/dvn/ncuspz/zsdehr
title: Table B4 Data.dat

description: :unav
DOI: 10.5281/zenodo.3519798
title: Use of Vegetation Change Tracker, Spatial Analysis, and Random Forest Regression to Assess the Evolution of Plantation Stand Age in Southeast China

description: It is crucial to determine the spatio-temporal distribution patterns of forest ages across wide regions, as forest management plans and practices, and ecosystem carbon budgeting are highly dependent on these. However, given frequent deforestation events (e.g., harvesting) and rapid recovery of plantation stands in Southern China, field-based forest age measurements over wide regions are time-consuming, labour-intensive, and costly. In the current study, we mapped the spatio-temporal patterns of forest stand ages across three typical plantations in Southern China. This was accomplished by using two new feasible and accurate methods, 1) integrating vegetation change tracker (VCT) algorithm and spatial analysis (VCT-SA) for the pixels that were disturbed at least once from 1987 to 2017, and 2) integrating VCT and random forest (VCT-RF) for the pixels were not disturbed during the study period. The results revealed the spatio-temporal distribution of age structure, which indicated that the plantation stands in our large study area were increasingly aging.
DOI: 10.5281/zenodo.3519799
title: Use of Vegetation Change Tracker, Spatial Analysis, and Random Forest Regression to Assess the Evolution of Plantation Stand Age in Southeast China

description: It is crucial to determine the spatio-temporal distribution patterns of forest ages across wide regions, as forest management plans and practices, and ecosystem carbon budgeting are highly dependent on these. However, given frequent deforestation events (e.g., harvesting) and rapid recovery of plantation stands in Southern China, field-based forest age measurements over wide regions are time-consuming, labour-intensive, and costly. In the current study, we mapped the spatio-temporal patterns of forest stand ages across three typical plantations in Southern China. This was accomplished by using two new feasible and accurate methods, 1) integrating vegetation change tracker (VCT) algorithm and spatial analysis (VCT-SA) for the pixels that were disturbed at least once from 1987 to 2017, and 2) integrating VCT and random forest (VCT-RF) for the pixels were not disturbed during the study period. The results revealed the spatio-temporal distribution of age structure, which indicated that the plantation stands in our large study area were increasingly aging.
DOI: 10.7910/dvn/ncuspz/hrcjil
title: Table A1 Data.dat

description: :unav
DOI: 10.7910/dvn/ncuspz/j6s2f4
title: Table A1 Column 1.inp

description: :unav
DOI: 10.7910/dvn/ncuspz/tt81jb
title: Table A2.out

description: :unav
DOI: 10.7910/dvn/h93zkk/bxxqcg
title: DB5.tar.gz

description: Pre-processed version of DB5.
DOI: 10.7910/dvn/m402tu/3xqnqw
title: Appendix.dta

description: :unav
DOI: 10.7910/dvn/m402tu/hnlwjj
title: figures_1_2.dta

description: :unav
DOI: 10.7910/dvn/m402tu/zo9mrn
title: Appendix.do

description: Replicates findings in the Appendix.
DOI: 10.7910/dvn/h93zkk/gvqod2
title: neurips_2019.pdf

description: Poster accompanying paper at NeurIPS 2019
DOI: 10.7910/dvn/m402tu/it7ouf
title: assn_lobbying.tab

description: A data file necessary for replicating the Appendix.
DOI: 10.7910/dvn/m402tu/wbb8uk
title: Fig1and2.do

description: This file makes Figures 1 and 2 in the body of the paper.
DOI: 10.15139/s3/52mijo
title: Northwestern Speed-Dating Study II, 2007

description: N = 187 Northwestern University undergraduates (93 women, 94 men) participated in one of eight speed-dating events. At each event, participants went on 4-minute dates with all 11-12 opposite-sex individuals who attended the event; they completed a 2-minute questionnaire at the end of each date. These dates were video- and audio-recorded. Prior to the speed-dating event, participants completed a 30-minute intake questionnaire. Following the speed-dating event, participants completed 12 follow-up surveys over the course of 16 weeks (i.e., 1 survey every 3 days for the first 5 surveys; 1 survey every 2 weeks for the subsequent 7 surveys).
DOI: 10.15139/s3/hk7kzq
title: Northwestern Speed-Dating Study I, 2005

description: N = 163 Northwestern University undergraduates (81 women, 82 men) participated in one of seven speed-dating events. At each event, participants went on 4-minute dates with all 9-13 opposite-sex individuals who attended the event; they completed a 2-minute questionnaire at the end of each date. These dates were NOT video- or audio-recorded. Prior to the speed-dating event, participants completed a 30-minute intake questionnaire. Following the speed-dating event, participants completed 10 follow-up surveys over the course of 30 days (i.e., one survey every three days).