cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.sut43u
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coelosphaerium confertum West & G.S.West"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002410-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18712/nsd-nsd1444-v3
title: Occupational Mobility, Career and Values, 1990

description: The survey's aim was to map out the labour market mobility, work activity/ passivity, part time work and reasons to this in the first ten year period after education. In addition, further education, attitude towards unions and work values were mapped out. The registered data are results from a questionnaire among “DH-economist”, half of the teachers, all the pre-school teachers, all the nurses, all female and half of the male engineers who were educated in 1978, all together 2569 persons.
DOI: 10.18712/nsd-nsd1618-v2
title: Diagnosis of Dementia at a Nursing Home in Tromsø, Norway, 1997

description: The purpose of the project was to draw attention to dementia in nursing homes, find the occurrence of dementia and compare the figures with previous dementia diagnosis in nursing homes
DOI: 10.18712/nsd-nsd2274-v2
title: EWS Launching and Consolidating a Nordic Research Agenda: Interdisciplinary, Empirical Research on Experiential Literary Reading, 2015

description: A crucial part of basic reading skills is so-called deep reading, i.e., continuous reading of long linear texts such as novels. Empirical research shows that literary deep reading in particular, by virtue of its appeal to first-person experience, yields unique cognitive and emotional benefits (enhancing or refining the capacity for sympathy and empathy, social inference, emotional self-regulation, verbal abilities and intelligence). The current decline in literary reading, combined with (possibly enhanced by) the systematic downplaying of experiential reading at all levels of literary education, form the background for this study. The project "EWS Launching and Consolidating a Nordic Research Agenda: Interdisciplinary, Empirical Research on Experiential Literary Reading, 2015" investigates literary reading and the consequences of specific reading strategies for education and, by extension, mental health. Leading international scholars contributed to launching an innovative, interdisciplinary Nordic research community. A first study was conducted in several Nordic countries simultaneously, and contrasted experiential literary reading against the more analytical approaches to literature typical for institutionalized literary instruction. High-quality inter-Nordic data on the nature of literary reading in educational settings was produced.

For further information about ”EWS Launching and Consolidating a Nordic Research Agenda: Interdisciplinary, Empirical Research on Experiential Literary Reading, 2015”, please contact the principal investigator.
DOI: 10.18712/nsd-nsd2722-v2
title: Neonate Ability for Monocyte Trained Immunity (NAMTI), 2018

description: It is shown that vaccines, for instance BCG, can give long term improvement of innate immune system responses. This study examined the ability of monocytes from neonates and adults to be "trained" by exposure to certain stimuli and "remember" this over time. An in vitro assay was used in this project to evaluate such responses. The responses where characterized by measuring secretion of key cytokines (TNF, IL-6 and IL-10) by monocytes after secondary stimuli, and describe differences between neonates and adults. This provides knowledge which is useful for potentiating the effects of vaccines, show the potential to evaluate optimal timeframe for vaccination and for prevention of serious infections among very young children.

This dataset contains data of cytokine levels expressed as fold changes over unsimulated cultures for adherent mononuclear cells, which have been stimulated with BCG and other antigens to measure their capacity to respond better to secondary stimuli. The data is given for 15 neonates and 30 adults. For adults, also age and gender is included.

Data are freely available for downloading.
DOI: 10.18712/nsd-nsd2814-v2
title: Adapting Coastal Zone Management to Ocean Acidification, 2016

description: Ocean acidification in concert with climate change and other anthropogenic stressors will lead to unprecedented and profound changes in coastal ecosystems. There is little knowledge of the processes of ocean acidification in Norwegian coastal areas, about the potential consequences, to what extent ocean acidification will interact with other ecosystem stressors, and how society may respond to this situation. Sustainable management of the coastal areas therefore hinge on the ability to address and mitigate ocean acidification and ocean acidification impacts. In order to make ocean acidification a governable issue, this project produced more knowledge about ocean acidification in the coastal zone, and gained new insight into how this knowledge can be co-produced with those who uses it for governance and industry purposes. Ocean acidification and climate change add uncertainties on several levels for coastal zone management, which raises the need for better knowledge on how governance regimes can operate in an effective way given such uncertainties. 

Through two case studies and measurements in coastal areas in southern and northern Norway, the project provides new knowledge about ocean acidification and ocean acidification impacts on coastal areas and develop models for how this knowledge can be used for coastal management. A sustainable economic development in Norway depends on well-functioning coastal zone management that are able to effectively respond to ocean acidification and other drivers of change. This project contributed to new and relevant knowledge to ensure such management. The project also assessed the ability of coastal management institutions to adapt to ocean acidification in a situation involving complex uncertainties. The studies in Norway were complemented by a knowledge exchange with Scotland, which allowed for comparisons across different coastal management systems facing similar ocean acidification-challenges. Stakeholder representatives were involved at all stages of the project. It is a transdisciplinary project, including marine scientists, anthropologists and environmental governance scholars.
DOI: 10.5281/zenodo.13828070
title: Supplementary Files to: Advances and shortfalls in the knowledge of Antarctic terrestrial biodiversity

description: Data files S1 to S4

S1. Antarctic eukaryotic species inventories with the year of description and first Antarctic discovery. CSV file.

S2. Antarctic biodiversity surveying effort. KnowBR completeness of spatial inventories (output grid values). CSV file.

S3. Antarctic biodiversity knowledge indicators database. XLSX file.

S4. Antarctic biodiversity knowledge gaps assessment. IDEA expert elicitation responses from the opinions of all the participant experts. CSV file.
DOI: 10.5281/zenodo.13828069
title: Supplementary Files to: Advances and shortfalls in the knowledge of Antarctic terrestrial biodiversity

description: Supporting data for: Advances and shortfalls in the knowledge of Antarctic terrestrial biodiversity. Pertierra et al. 2024 Science.

SUPPORTING FILE 1: BIODIVERSITY CHECKLIST (.xlsx). Antarctic species discovery rates (data).

SUPPORTING FILE 2: SACs R CODE (R.). Antarctic species discovery rates (code).

SUPPORTING FILE 3: ANTARCTIC INVENTORIES SPATIAL COMPLETENESS (.xlsx’). Spatial inventory completeness analysis (spatial results).

SUPPORTING FILE 4: SPATIAL COMPLETENESS R CODE (.R) Spatial inventory completeness analysis (code)

SUPPORTING FILE 5: INDICATOR DATABASE (.xlsx’). Summary info (data) with the number of entries retrieved per ecological shortfall (see specific code in 6-9).

SUPPORTING FILE 6: ABIOTIC TOLERANCE DATA RETRIEVAL WOS CODE (.txt). Search queries made to detect information about Antarctic species thermal tolerances.

SUPPORTING FILE 7: GENETIC DATA RETRIEVAL PEARL CODE (.txt) Genetic sequences data retrieval code executed for all Antarctic species in Genbank

SUPPORTING FILE 8: BIOTIC INTERACTION DATA RETRIEVAL R CODE (.R). Code for retrieving biotic interaction and ecological network data reported data per Antarctic species in GLOBI

SUPPORTING FILE 9: DATA MOBILIZATION VENN DIAGRAMS R CODE (.R) Diagrams of biological data mobilization to centralized meta-repositories (code)

SUPPORTING DATA FILE 10: EXPERT ELICITATION ON ANTARCTIC ECOLOGICAL KNOWLEDGE (.csv). Expert elicitations of ecological knowledge shortfalls by biodiversity group (scores)

SUPPORTING FILE 11: EXPERT ELICITATION R CODE (.R) Expert elicitations of ecological knowledge shortfalls by biodiversity group (code)

README (txt.)
DOI: 10.5281/zenodo.13988131
title: Supplementary Files to: Advances and shortfalls in the knowledge of Antarctic terrestrial biodiversity

description: Supporting data for: Advances and shortfalls in the knowledge of Antarctic terrestrial biodiversity. Pertierra et al. 2024 Science.

SUPPORTING FILE 1: BIODIVERSITY CHECKLIST (.xlsx). Antarctic species discovery rates (data).

SUPPORTING FILE 2: SACs R CODE (R.). Antarctic species discovery rates (code).

SUPPORTING FILE 3: ANTARCTIC INVENTORIES SPATIAL COMPLETENESS (.xlsx’). Spatial inventory completeness analysis (spatial results).

SUPPORTING FILE 4: SPATIAL COMPLETENESS R CODE (.R) Spatial inventory completeness analysis (code)

SUPPORTING FILE 5: INDICATOR DATABASE (.xlsx’). Summary info (data) with the number of entries retrieved per ecological shortfall (see specific code in 6-9).

SUPPORTING FILE 6: ABIOTIC TOLERANCE DATA RETRIEVAL WOS CODE (.txt). Search queries made to detect information about Antarctic species thermal tolerances.

SUPPORTING FILE 7: GENETIC DATA RETRIEVAL PEARL CODE (.txt) Genetic sequences data retrieval code executed for all Antarctic species in Genbank

SUPPORTING FILE 8: BIOTIC INTERACTION DATA RETRIEVAL R CODE (.R). Code for retrieving biotic interaction and ecological network data reported data per Antarctic species in GLOBI

SUPPORTING FILE 9: DATA MOBILIZATION VENN DIAGRAMS R CODE (.R) Diagrams of biological data mobilization to centralized meta-repositories (code)

SUPPORTING DATA FILE 10: EXPERT ELICITATION ON ANTARCTIC ECOLOGICAL KNOWLEDGE (.csv). Expert elicitations of ecological knowledge shortfalls by biodiversity group (scores)

SUPPORTING FILE 11: EXPERT ELICITATION R CODE (.R) Expert elicitations of ecological knowledge shortfalls by biodiversity group (code)

README (txt.)
DOI: 10.6084/m9.figshare.23960832
title: Regulatory Guidance on Randomization and the Use of Randomization Tests in Clinical Trials: A Systematic Review

description: Randomization is a critical aspect of the clinical trial. Regulatory guidance plays a role in clinical research. Randomization tests provide valid methodology for statistical inference. In the present paper, we intended to survey: (a) information contained in regulatory guidance on randomization; and (b) the use of randomization tests in trials supporting marketing applications. This systematic review used the Cortellis Regulatory Intelligence database (IDRAC). For (a), of <i>n</i> = 156 guidance documents, nine provided recommendations on randomization methods. For (b), <i>n</i> = 48 trials (52 submissions) employed randomization tests. 40 (83.3%) were phase III trials, 31 (64.6%) employed dynamic allocation. Randomization test was the primary in 5 (10.4%), and sensitivity analysis in 34 (70.8%) trials. Furthermore, randomization tests were performed when treatment allocation was not according to plan (4 (8.3%)), or violations of model assumptions (5 (10.4%)) were observed. Overall, there are sparse recommendations on randomization in current regulatory guidance, with little mention of recently developed methods which might outperform current practice in certain contexts. Greater adoption of such methods in pharmaceutical industry trials may lead to a better shared sense between regulators and trial sponsors on their appropriate use. Randomization tests are employed with greater frequency, reflecting increased appreciation of the validity and value of randomization tests.
DOI: 10.6084/m9.figshare.23960832.v1
title: Regulatory Guidance on Randomization and the Use of Randomization Tests in Clinical Trials: A Systematic Review

description: Randomization is a critical aspect of the clinical trial. Regulatory guidance plays a role in clinical research. Randomization tests provide valid methodology for statistical inference. In the present paper, we intended to survey: (a) information contained in regulatory guidance on randomization; and (b) the use of randomization tests in trials supporting marketing applications. This systematic review used the Cortellis Regulatory Intelligence database (IDRAC). For (a), of <i>n</i> = 156 guidance documents, nine provided recommendations on randomization methods. For (b), <i>n</i> = 48 trials (52 submissions) employed randomization tests. 40 (83.3%) were phase III trials, 31 (64.6%) employed dynamic allocation. Randomization test was the primary in 5 (10.4%), and sensitivity analysis in 34 (70.8%) trials. Furthermore, randomization tests were performed when treatment allocation was not according to plan (4 (8.3%)), or violations of model assumptions (5 (10.4%)) were observed. Overall, there are sparse recommendations on randomization in current regulatory guidance, with little mention of recently developed methods which might outperform current practice in certain contexts. Greater adoption of such methods in pharmaceutical industry trials may lead to a better shared sense between regulators and trial sponsors on their appropriate use. Randomization tests are employed with greater frequency, reflecting increased appreciation of the validity and value of randomization tests.
DOI: 10.6084/m9.figshare.24030171
title: Statistical Inference for Vaccine Efficacy: A Re-Randomization Procedure to Analyse Poisson Outcomes under Covariate-Adaptive Randomization

description: Re-randomization inference is used as an alternative approach to more traditional statistical methods. Free from parametric assumptions, its use is particularly suited for studies incorporating covariate-adaptive randomization, and can provide additional evaluation and confirmation of inferences drawn from the original analyses, for example, as a sensitivity analysis. We discuss methodological and computational aspects in the context of a Poisson regression and describe an approach to re-randomization inference. This is tested in a simulation study and then illustrated in a case study in which we evaluate vaccine efficacy data from a previously published influenza vaccine study. Our simulations indicate that re-randomization inference corrects for model misspecification. The case study, which accounted for the minimization factors, shows that the <i>p</i>-value and confidence limits from re-randomization inference agree with the original analysis. In conclusion re-randomization inference is a useful method that can be used to support vaccine clinical development.
DOI: 10.6084/m9.figshare.24030171.v2
title: Statistical Inference for Vaccine Efficacy: A Re-Randomization Procedure to Analyse Poisson Outcomes under Covariate-Adaptive Randomization

description: Re-randomization inference is used as an alternative approach to more traditional statistical methods. Free from parametric assumptions, its use is particularly suited for studies incorporating covariate-adaptive randomization, and can provide additional evaluation and confirmation of inferences drawn from the original analyses, for example, as a sensitivity analysis. We discuss methodological and computational aspects in the context of a Poisson regression and describe an approach to re-randomization inference. This is tested in a simulation study and then illustrated in a case study in which we evaluate vaccine efficacy data from a previously published influenza vaccine study. Our simulations indicate that re-randomization inference corrects for model misspecification. The case study, which accounted for the minimization factors, shows that the <i>p</i>-value and confidence limits from re-randomization inference agree with the original analysis. In conclusion re-randomization inference is a useful method that can be used to support vaccine clinical development.
DOI: 10.6084/m9.figshare.25145289
title: Bayesian and Frequentist Approaches to Rescuing Disrupted Trials: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions

description: The COVID-19 pandemic impacted clinical trials in ways never expected. However, similar challenges should now be expected going forward. These challenges made us aware of statistical problems arising from other types of disruptions that had not previously captured the attention of the statistical community. This article describes some frequentist and Bayesian statistical tools that can be used with future disruptions and illuminates issues that could benefit from more statistical research. Disruptions may threaten a clinical trial’s validity. Here, we address two resultant challenges: (a) performing an unplanned analysis with options to stop and/or change the sample size; and (b) changes in the study population that are observable or unobservable at the patient level. Different paradigms lead to different ways of doing things, but many statisticians work exclusively within a Bayesian or frequentist paradigm. We propose and provide side-by-side descriptions of Bayesian and frequentist approaches to dealing with these challenges. An illustrative phase III trial aims to compare second-line therapies for type 2 diabetes. We compare and contrast Bayesian and frequentist coping strategies assuming the trial was interrupted due to COVID-19, focusing on Type I error control and the expected loss from a specific utility function.
DOI: 10.6084/m9.figshare.25145289.v1
title: Bayesian and Frequentist Approaches to Rescuing Disrupted Trials: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions

description: The COVID-19 pandemic impacted clinical trials in ways never expected. However, similar challenges should now be expected going forward. These challenges made us aware of statistical problems arising from other types of disruptions that had not previously captured the attention of the statistical community. This article describes some frequentist and Bayesian statistical tools that can be used with future disruptions and illuminates issues that could benefit from more statistical research. Disruptions may threaten a clinical trial’s validity. Here, we address two resultant challenges: (a) performing an unplanned analysis with options to stop and/or change the sample size; and (b) changes in the study population that are observable or unobservable at the patient level. Different paradigms lead to different ways of doing things, but many statisticians work exclusively within a Bayesian or frequentist paradigm. We propose and provide side-by-side descriptions of Bayesian and frequentist approaches to dealing with these challenges. An illustrative phase III trial aims to compare second-line therapies for type 2 diabetes. We compare and contrast Bayesian and frequentist coping strategies assuming the trial was interrupted due to COVID-19, focusing on Type I error control and the expected loss from a specific utility function.
DOI: 10.6084/m9.figshare.24171453
title: Balancing the Objectives of Statistical Efficiency and Allocation Randomness in Randomized Controlled Trials

description: Various restricted randomization procedures are available to achieve equal (1:1) allocation in a randomized clinical trial. However, for some procedures, there is a nonnegligible probability of imbalance in the final numbers which may result in an underpowered study. It is important to assess such probability at the study planning stage and make adjustments in the design if needed. In this article, we perform a quantitative assessment of the tradeoff between randomness, balance, and power of restricted randomization designs targeting equal allocation. First, we study the small-sample performance of biased coin designs with known asymptotic properties and identify a design with an excellent balance–randomness tradeoff. Second, we investigate the issue of randomization-induced treatment imbalance and the corresponding risk of an underpowered study. We propose two risk mitigation strategies: increasing the total sample size or fine-tuning the biased coin parameter to obtain the least restrictive randomization procedure that attains the target power with a high, user-defined probability for the given sample size. Additionally, we investigate an approach for finding the most balanced design that satisfies a constraint on the chosen measure of randomness. Our proposed methodology is simple and yet generalizable to more complex settings, such as trials with stratified randomization and multi-arm trials with possibly unequal randomization ratios.
DOI: 10.6084/m9.figshare.24171453.v1
title: Balancing the Objectives of Statistical Efficiency and Allocation Randomness in Randomized Controlled Trials

description: Various restricted randomization procedures are available to achieve equal (1:1) allocation in a randomized clinical trial. However, for some procedures, there is a nonnegligible probability of imbalance in the final numbers which may result in an underpowered study. It is important to assess such probability at the study planning stage and make adjustments in the design if needed. In this article, we perform a quantitative assessment of the tradeoff between randomness, balance, and power of restricted randomization designs targeting equal allocation. First, we study the small-sample performance of biased coin designs with known asymptotic properties and identify a design with an excellent balance–randomness tradeoff. Second, we investigate the issue of randomization-induced treatment imbalance and the corresponding risk of an underpowered study. We propose two risk mitigation strategies: increasing the total sample size or fine-tuning the biased coin parameter to obtain the least restrictive randomization procedure that attains the target power with a high, user-defined probability for the given sample size. Additionally, we investigate an approach for finding the most balanced design that satisfies a constraint on the chosen measure of randomness. Our proposed methodology is simple and yet generalizable to more complex settings, such as trials with stratified randomization and multi-arm trials with possibly unequal randomization ratios.
DOI: 10.6084/m9.figshare.24030171.v1
title: Statistical inference for vaccine efficacy: a re-randomization procedure to analyse Poisson outcomes under covariate-adaptive randomization.

description: Re-randomization inference is used as an alternative approach to more traditional statistical methods. Free from parametric assumptions, its use is particularly suited for studies incorporating covariate-adaptive randomization, and can provide additional evaluation and confirmation of inferences drawn from the original analyses, e.g., as a sensitivity analysis. We discuss methodological and computational aspects in the context of a Poisson regression and describe an approach to re-randomization inference. This is tested in a simulation study and then illustrated in a case study in which we evaluate vaccine efficacy data from a previously published influenza vaccine study. Our simulations indicate that re-randomization inference corrects for model misspecification. The case study, which accounted for the minimization factors, shows that the P-value and confidence limits from re-randomization inference agree with the original analysis. In conclusion re-randomization inference is a useful method that can be utilized to support vaccine clinical development.