Incomplete List Research Articles

Исследование проблем формирования региональной потребительской корзины

The article touches upon the problem of forming the consumer goods basket, which is an important social factor determining the living cost of the population. Analysis of the methods of calculating the consumer goods basket in the Russian Federation and in the Astrakhan region has shown that food products make up 50% of it, which is 2.5 times higher than their share in consumer goods baskets of economically developed countries. In terms of the variety of products and services, the consumer goods basket in Russia is a clear outsider: it contains 156 items against 
 350 - 475 items in Western Europe and the United States. It can be considered a consumer goods basket of the poor, because it only provides an opportunity to survive in conditions of austerity. The comparative analysis of food products included in the basket of the Astrakhan region and recommended by the Ministry of health of the Russian Federation revealed significant deviations from the rational consumption standards. Their observance will increase the living cost of different categories of population in the region from 4.5% to 20% and require an increase in regional budget expenditures for providing social support measures by 15%. It has been inferred that the dual role 
 of the food basket in the economy is explained by two opposite goals: social and budgetary. The goals of social development dictate the establishment of the volume of food consumption in accordance with scientific recommendations. The goals of budget savings lead to underestimation 
 of the basket cost due to using a limited number of cheap products and an incomplete list of goods and services for normal human life. It is necessary to review the composition of the consumer goods basket in favor of a healthier and more useful set of products, expanding the range of non-food items and the list of services. The expansion of the consumer basket can become an effective factor in the growth of consumption volumes, the growth of business income, taxes and the state budget, reach the higher living standards in accordance with the requirements of the social market economy

Generically speaking, a survey on Neogene rodent diversity at the genus level in the NOW database

Over the last half a century, a massive amount of data has been gathered on Neogene rodents of Europe. Using the NOW database, we analysed changes in generic diversity during the Neogene and the beginning of the Quaternary. Studies as the present are useful for exploring major changes in diversity, but the pitfalls are many and varied. Whereas the quality of the fossil record is good, there are notable exceptions. Within our dataset, MN 1, MN 12 and MN 17 stand out for the limited number of localities available and the record of the eastern Mediterranean is clearly as yet poorer than that from central Europe and the Iberian Peninsula. The record can be influenced by incomplete faunal lists, outdated literature and unresolved taxonomies. In addition, the use of the MN system presumably obscures patterns, as it often does not allow for a co-eval comparison between various regions. Reconstruction of major patterns starts with the understanding of basic data. Despite all these limitations the results of this work indicate that the record for central Europe consistently shows higher diversity than lower latitudes. The highest peak in diversity is found in MN 15, but the record of the Iberian Peninsula shows no increase at that time. The rodent diversity is surprisingly constant during most part of the Neogene, the stronger variations being related to the diversification of the murinae and arvicolinae groups and decline of the cricetine.

To the problem of the subject of reflection of justice and its structure

This scientific article discusses problematic issues about the subject of reflection of justice and its structure. In particular, the author argues that justice as a set of ideas and feelings expresses its attitude not only to the current and desirable law, but also to the law of the past. In this case, we are talking about assessing the historical legal sources of law, their effectiveness. It is emphasized that in order to present the subject of reflection of legal awareness in a holistic manner, focusing only on its legal aspect, without resorting to listing any legal elements included in it, to avoid their uncertain incomplete lists, one should use the category of legal validity (legal reality, legal a life). Moreover, given the close relationship between the state and law, their interaction in various forms, the subject of reflection of legal consciousness should be defined through the category of “state-legal reality (reality, life)”. With regard to the problem of the structure of legal consciousness, focusing on the traditional and generally accepted isolation of two elements in it - legal psychology and legal ideology, it is noted that the main position, which has methodological significance, is that these elements are interrelated, they coexist, although their ratio may be very different, and the question of the dominance of one of these elements should be resolved dialectically, giving arguments in favor of both the first and second.

Matching formulation of the Staff Transfer Problem: meta-heuristic approaches

In this paper, the Staff Transfer Problem (STP) in Human Resource Management is addressed as a stable matching problem. Earlier, formulation of this problem was of scheduling/allocation type. Here, the stable matching formulation is completely a new and more practical approach to the problem. This new formulation involves two preference lists: the first list contains the offices/locations preferred by the employees undergoing transfer and the second list contains the employees preferred by the employer of an office/location where those employees want to be transferred. The capacity of an office/location would act as a hard constraint. While matching these two lists, the objective is to maximize the number of transfers and at the same time to stabilize the matching, i.e., to minimize the number of blocking pairs. The resulting STP instance belongs to an instance of Maximum Size Minimum Blocking Pair Stable Matching with incomplete preference list (MAX SIZE MIN BP SMI) and has been proved in this paper to be NP-hard. As the problem is new in formulation, no previous work, method or result is available. There was no preference in selecting meta-heuristics. Among a large number of existing meta-heuristics, some most widely used meta-heuristics, namely, Simulated Annealing, Genetic Algorithms, Tabu Search and some variants of them have been chosen. Based on them four meta-heuristic approaches have been proposed, namely, btSA_match, gtSA_match, GA_match and TS_match. The variants btSA_match and gtSA_match are obtained from modifications made upon Simulated Annealing. EGA_match and TS_match are based on modified Genetic Algorithms and Tabu Search respectively. As there is no previous result in the existing literature, the performance has been compared among these four methods. It is observed that, variants of Simulated Annealing (SA) outperform others w.r.t. the performance metrics. The SA-variant with greedy nature, incorporated with a tabu list (gtSA_match) has shown that the best result on the basis of statistical analysis.

Correction to: Cant in the interpupillary line.

The above letter, published in the 8 November issue (2019; 762) gave an incomplete list of authors. The correct list of authors is as follows: V. Sathya Sree, R. Saravanan, S. Deepshika, K. Muthu, Coimbatore, India.

Planning the activities of the utility vehicles department in the structure of a joint stock company

Planning the activities of a structural unit is one of the sources for finding reserves to improve the efficiency of the company as a whole. The correctness of the methods used, the completeness of the source data, the software used is an incomplete list of factors affecting the reliability of the plans of the company’s departments, which in turn make up a plan of the organization’s activity as a whole. The article provides an overview of the planning process for the Utility Vehicles Department, considers planning tools, the possibility of increasing the efficiency of the process and achieving planned indicators.

Fault Prediction of Fan Gearbox Based on K-Means Clustering and LSTM

The traditional fault prediction model of wind turbine equipment mainly aims to establishing the degradation characteristic curve of the wind turbine, and draws conclusions from the analysis of the curve. However, in the actual industry, the wind turbine operating data has a high degree of nonlinear complexity and the traditional enterprises pay less attention to this aspect, which leads to partial loss in the fault characterization and serious loss in the label data. This makes the previous data processing more difficult, and it also causes the accuracy of the later prediction results to be inferior. Therefore, this paper uses k-means clustering algorithm to process the original running data into K clusters, and then comprehensively analyzes the cluster results and the provided incomplete fault list to extract useful information. The data is built to fit the Long Short-Term Memory (LSTM) model predictions. Comparing the prediction results with the SVRM method reveals that LSTM has certain advantages in fault prediction for the data in this paper.

Random Popular Matchings with Incomplete Preference Lists

Given a set $A$ of $n$ people and a set $B$ of $m \geq n$ items, with each person having a list that ranks his/her preferred items in order of preference, we want to match every person with a unique item. A matching $M$ is called popular if for any other matching $M'$, the number of people who prefer $M$ to $M'$ is not less than the number of those who prefer $M'$ to $M$. For given $n$ and $m$, consider the probability of existence of a popular matching when each person's preference list is independently and uniformly generated at random. Previously, Mahdian[Mahdian, Conf. El. Comm., 2006] showed that when people's preference lists are strict (containing no ties) and complete (containing all items in $B$), if $\alpha = m/n > \alpha_*$, where $\alpha_* \approx 1.42$ is the root of equation $x^2 = e^{1/x}$, then a popular matching exists with probability $1-o(1)$; and if $\alpha < \alpha_*$, then a popular matching exists with probability $o(1)$, i.e. a phase transition occurs at $\alpha_*$. In this paper, we investigate phase transitions in the case that people's preference lists are strict but not complete. We show that in the case where every person has a preference list with length of a constant $k \geq 4$, a similar phase transition occurs at $\alpha_k$, where $\alpha_k \geq 1$ is the root of equation $x e^{-1/2x} = 1-(1-e^{-1/x})^{k-1}$.

IS OUR MED-REC A MED-WRECK? QUALITY IMPROVEMENT STUDY

SESSION TITLE: Tuesday Abstract Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/22/2019 01:00 PM - 02:00 PM PURPOSE: To improve patient care during hospitalization and decrease readmission rates. METHODS: This study was performed at Saint Peter’s University Hospital during the months of June- September 2018. Patient charts were randomly identified and reviewed by two physician residents (RC, JJ). Home medications were identified based on information provided by the patient, caregivers, and documents from the PCP’s office and/or patient’s pharmacy. Medication reconciliation was deemed accurate if there was 100% concurrence between the medication intake performed by the admitting staff and the reconciliation performed by the quality improvement team. All data was entered in Microsoft Excel. RESULTS: A total of 40 charts were reviewed in the study period. The mean age was 68±19.6 years, 25 (63.5%) patients were Caucasians, 6 (15%) were African-American, 6 (15%) others and 3 (7.5%) patients refused to answer. 21 males (52.5%). 35 (87.5%) spoke English, while the primary language of others was Spanish (1), Korean (1), Filipino (1), Mandarin (1), Vietnamese (1). 21 were daytime admissions (52.5%) and 19 were nighttime admissions (47.5 %). 25 (62.5%) admission medication reconciliations were accurate, 14 (35%) were inaccurate, and 1 (2.5%) was an outlier. For the daytime admissions, 61.9% were accurate and 38.1% were inaccurate. Of the nighttime admissions, 63.15% were accurate, 31.57% were inaccurate, and 5.26% was an outlier. Of the fifteen charts with a medication reconciliation errors incomplete list (53%), dosing errors (40%) and wrong medication (7%) were the causes of inaccuracy. The main causes for inaccurate medication reconciliation were reliability on patient knowledge of his or her own meds, unreported over-the-counter medications, initial reconciliation performed by different hospital staff (nurses, pharmacist, nurse aids, ED physicians), medications not double checked with pharmacies or primary care physicians, lack of time for patient encounters, and language barriers. CONCLUSIONS: Medication errors exist despite electronic medication reconciliation. Reconciliation errors were equal despite the time of admission. At the end of our study we concluded there should be a person designated for medication reconciliation of the patients admitted into the hospital. CLINICAL IMPLICATIONS: Medication errors are one of the leading causes of injury to hospital patients, and chart reviews reveal that over half of all hospital medication errors occur at different interfaces of care. Medication reconciliation process involves verification, clarification, and reconciliation. We conducted this quality improvement project to identify how accurate is our admission Medication intake process and evaluate the different causes of inaccuracy. DISCLOSURES: No relevant relationships by Rafael Caputi, source=Web Response No relevant relationships by Jose Jimenez Zuluaga, source=Web Response No relevant relationships by Janani Mohan, source=Web Response

THE INFLUENCE OF THE THERMAL REDUCTION TEMPERATURE ON THE STRUCTURE AND ELECTROPHYSICAL PROPERTIES OF REDUCED GRAPHENE OXIDE FILMS

Introduction. An incomplete list of graphene properties includes high electric conductivity, thermal conductivity, strength, large surface area, high light transmittance. Graphene is a very promising material from the point of view of its application in micro- and nanoelectronics. In addition, graphene advantage is a possibility of its obtaining by various ways. It allows creating materials with desired physicochemical properties by using appropriate technological methods. Objective. The investigation of a thermal reduction temperature influence on physicochemical properties of graphene oxide (GO) films. Materials and methods. In the present work, GO films are obtained on a slide surface by its immersing and removing from a graphene oxide water dispersion (dip coating). Obtained samples are studied by methods of scanning electron microscopy, Raman spectroscopy, and elemental CHN analysis. A sheet resistance is measured by a four-point probes method. Results. A content difference of elements (C, H, N) in studied samples, and both graphene structure defectiveness and sheet resistance decrease, are found to be proportional to a reduction temperature increase. A GO films thickness decrease during a heat treatment is also observed, which is presumably associated with a functional GO groups loss while thermal reduction. Conclusion. Research results demonstrate a possibility of a carbon films with desired physicochemical properties obtaining from a reduced graphene oxide (RGO), which can be used in thin-film technologies. Presented materials can also be useful in issues related to GO and RGO obtaining and applying.

Effect of acid-reducing agents on the efficacy of capecitabine in metastatic gastrointestinal cancers.

e15058 Background: Recent retrospective and subgroup analyses have evaluated the effects of capecitabine with acid-reducing agents both in the adjuvant setting for colon cancer and in the palliative setting for stage IV gastroesophageal malignancies. Efficacy outcomes in these studies are contradictory. Acid-reducing agents are thought to reduce the absorption of capecitabine by increasing gastric pH leading to a concern of decreased efficacy. Studies thus far have not included stage IV colorectal cancers, a common population who receives capecitabine-based regimens. Methods: We conducted a retrospective chart review of patients diagnosed with stage IV Gastro Intestinal (GI) cancers treated with capecitabine-based therapies between 2012 and 2018. Electronic health records were used for data collection. Descriptive statistics and COX regression model were utilized for data analysis. Results: Of the 249 charts that were screened for inclusion, 58 were included in this review. Thirty-eight (65.5%) had a diagnosis of colon cancer, 11 (19%) had rectal cancer, and 9 (15.5%) had other GI malignancies. The most common capecitabine-based regimens included XELOX alone (29%) or with bevacizumab (36%). During capecitabine treatment, 20 (34.5%) patients received concomitant acid-reducing therapy. This included 19 patients taking a PPI and 1 patient taking a H2 Inhibitor. Patients who did not receive acid-reducing therapy had a 1-year PFS of 23.7% compared to 25% in patients who did not, (HR 0.55, p = 0.46). The 1-year OS was 68.4% in the non-acid-reducing agent group and 60% in the patients who did receive acid-reducing agents during capecitabine treatment, respectively (HR 0.17, p = 0.68). Conclusions: Receiving acid-reducing agents concomitantly with capecitabine-based regimens appears to not have an effect on 1-year PFS or OS in patients with Stage IV GI cancers. These outcomes may have been affected by the sample size, incomplete home medication lists, and compliance issues with capecitabine. Larger population studies are needed to validate these findings and identify the significance of utilization of acid-reducing agents in patients with Stage IV GI cancers receiving capecitabine.

Constructing continuum-like measures based on a nonlocal lattice particle model: Deformation gradient, strain and stress tensors

Explicit expressions for continuum-like measures of deformation gradient, strain and stress tensors were constructed using the techniques of weighted least squares and energy conjugate. Although presented based on a nonlocal lattice particle model, the formulations of these measures are general in nature and can be applied to other numerical models. Deformation gradient was formulated based on the deformation states of neighboring material points. Within the small strain limit, the infinitesimal strain tensor was derived from normal strains of bonds connecting material point of interest with all its neighbors. The second Piola–Kirchhoff stress tensor was constructed using the energy conjugate concept with respect to Green–Lagrangian strain tensor. The first Piola–Kirchhoff and Cauchy stress tensors were also formulated based on the derived second Piola–Kirchhoff stress tensor. For problems of homogeneous and inhomogeneous deformations, all three constructed measures yield very good predictions comparing to local continuum mechanics solutions. However, the second Piola–Kirchhoff formulation predicts less accurate results in surface regions due to incomplete neighbor list of material points with these regions.

A Method for Aggregating Ranked Services for Personal Preference Based Selection

Typically, users' service requests, which are similar with varying preferences on non-functional attributes, may result in ranked lists of services that partially meet their needs due to conflicting non-functional attributes. The resultant multiple ranked lists of services that partially satisfies the user's request makes it challenging for the user to choose an optimal service, based on his/her preference. This work proposes a method that aggregates multiple ranked lists of services into a single aggregated ranked list, where top ranked services are selected for the user. Two algorithms are proposed; 1) Rank Aggregation for Complete Lists (RACoL), that aggregates complete ranked lists and 2) Rank Aggregation for Incomplete Lists (RAIL) to aggregate incomplete ranked lists. Examples using real-world airline services to evaluate both algorithms show that the results from both proposed algorithms closely represent the sets of ranked lists better than using alternative approaches. Experiments were also carried out to validate their performance.

Pembinaan Iklim Sekolah K-7 Sebagai Upaya Meningkatkan Efektivitas Belajar: Best Practises

Seven-K School Climate Development as an Effort to Improve the Effectiveness of Learning in Pasaman District managerial schools, as well as how teachers and students attempt to utilize the climate and school culture as a source of learning. For Citizenship Education (PKn) teachers and Social Sciences (IPS) teachers. Principal's leadership, influenced by supervision, school climate, and community support. Aspects of school discipline need to be improved, as seen from the incomplete recap of the presence of teachers and staff; the absence of student records that violate the code of conduct; the absence of proof of examination of teacher and employee assignments by the principal; not all teachers make learning tools (only 50-60%); incomplete list of teachers attending the flag ceremony; there is no government regulation (PP 30/1980) regarding the rules of civil servants; there are no programs and documents giving rewards and punishment to teachers and employees. In the field of management: incomplete description of the tasks of each organization; there is no evaluation book on the implementation of school programs, not yet transparent school financial management. In the field of Seventh-K (K7) (cleanliness, beauty, order, safety, family, shade, and health) there are still findings such as student toilet cleanliness that is poorly maintained, adequate trash bins are not yet available, school gardens are poorly maintained, many students are late at hours first, picket teachers have not been functioning to improve discipline, and school yearning has not been sufficient In terms of output or quantitative learning outcomes, it has also not shown encouraging results. The 2018 UN results for the junior high school level, the writer's managerial area reached a graduation rate of 93.81%. Although UN results can be categorized as good because the graduation rate reaches 95.78% (2017); 96.59% (2018), but the results are almost positively correlated with high school graduation rates.

Mathematical models for stable matching problems with ties and incomplete lists

We present new integer linear programming (ILP) models for NP-hard optimisation problems in instances of the Stable Marriage problem with Ties and Incomplete lists (SMTI) and its many-to-one generalisation, the Hospitals/Residents problem with Ties (HRT). These models can be used to efficiently solve these optimisation problems when applied to (i) instances derived from real-world applications, and (ii) larger instances that are randomly-generated. In the case of SMTI, we consider instances arising from the pairing of children with adoptive families, where preferences are obtained from a quality measure of each possible pairing of child to family. In this case, we seek a maximum weight stable matching. We present new algorithms for preprocessing instances of SMTI with ties on both sides, as well as new ILP models. Algorithms based on existing state-of-the-art models only solve 6 of our 22 real-world instances within an hour per instance, and our new models incorporating dummy variables and constraint merging, together with preprocessing and a warm start, solve all 22 instances within a mean runtime of a minute. For HRT, we consider instances derived from the problem of assigning junior doctors to foundation posts in Scottish hospitals. Here, we seek a maximum size stable matching. We show how to extend our models for SMTI to HRT and reduce the average running time for real-world HRT instances by two orders of magnitude. We also show that our models outperform by a wide margin all known state-of-the-art models on larger randomly-generated instances of SMTI and HRT.

Fuzzy Approach to Student-Project Allocation (SPA) Problem

This paper presents a novel algorithm for solving a Student-Project Allocation problem, a variation of a two-sided matching algorithm, where a large number of students are allocated to numerous projects with limited available allocation places. Several new or improved algorithms are proposed, inspired by recommender systems and combined into a genetic algorithm. The main two algorithms are (i) variating the master list of student average grade ranking inspired by a fuzzy approach and (ii) extending the incomplete project preference lists by exploring the similarities of student choices, thus minimizing the number of randomly allocated students. The algorithm was implemented for allocating more than 500 students to more than 200 projects, in a course at the University of Zagreb, Faculty of Electrical Engineering and Computing. We compared our algorithm with the Deferred Acceptance (DA) Algorithm to check its validity. Using the fuzzy approach, the number of unallocated students decreased by 10%, with almost no effect to the top-ranked students. The combined usage of all proposed algorithms increased the number of successfully allocated students by more than 25%.

Аналітика великих даних: принципи, напрямки і задачі (огляд)

We review directions (avenues) of Big Data analysis and their practical meaning as well as problems and tasks in this field. Big Data Analytics appears a dominant trend in development of modern information technologies for management and planning in business. A few examples of real applications of Big Data are briefly outlined. Analysis of Big Data is aimed to extract useful sense from raw data collection. Big Data and Big Analytics have evolved as computer society’s response to the challenges raised by rapid grows in data volumes, variety, heterogeneity, velocity and veracity. Big Data Analytics may be seen as today’s phase of researches and developments known under names ‘Data Mining’, ‘Knowledge Discovery in Data’, ‘intelligent data analysis’ etc. We suggest that there exist three modes of large-scale usage of Big Data: 1) ‘intelligent information retrieval; 2) massive “intermediate” data processing (concentration, mining), which may be performed during one or two scanning; 3) model inference from data; 4) knowledge discovery in data. Stages in data analysis cycle are outlined. Because of Big Data are raw, distributed, unstructured, heterogeneous and disaggregated (vertically splitted), this data should be prepared for deep analysis. Data preparation may comprise such jobs as data retrieval, access, filtering, cleaning, aggregation, integration, dimensionality reduction, reformatting etc. There are several classes of typical data analysis problems (tasks), including: cases grouping (clustering), predictive model inference (regression, classification, recognition etc.), generative model inference, extracting structures and regularities from data. Distinction between model inference and knowledge discovery is elucidated. We give some suggestion why ‘deep learning’ (one of the most attractive topic by now) is so successive and popular. One of drawbacks of traditional models is they disability to make prediction under incomplete list of predictors (when some predictors are missed) or under augmented list of predictors. One may overcome this drawback using causal model. Causal networks are illuminated in the survey as attractive in that they appear to be expressive generative models and (simultaneously) predictive models in strict sense. This means they pretend to explain how the object at hand is acting (provided they are adequate). Being adequate, causal network facilitates predicting causal effect of local intervention on the object. Methods used in Big Data Analytics will be reviewed in the next paper.

Vector Generation of Quantum Contextual Sets in Even Dimensional Hilbert Spaces.

Recently, quantum contextuality has been proved to be the source of quantum computation’s power. That, together with multiple recent contextual experiments, prompts improving the methods of generation of contextual sets and finding their features. The most elaborated contextual sets, which offer blueprints for contextual experiments and computational gates, are the Kochen–Specker (KS) sets. In this paper, we show a method of vector generation that supersedes previous methods. It is implemented by means of algorithms and programs that generate hypergraphs embodying the Kochen–Specker property and that are designed to be carried out on supercomputers. We show that vector component generation of KS hypergraphs exhausts all possible vectors that can be constructed from chosen vector components, in contrast to previous studies that used incomplete lists of vectors and therefore missed a majority of hypergraphs. Consequently, this unified method is far more efficient for generations of KS sets and their implementation in quantum computation and quantum communication. Several new KS classes and their features have been found and are elaborated on in the paper. Greechie diagrams are discussed.

Incomplete species lists derived from global and regional specimen‐record databases affect macroecological analyses: A case study on the vascular plants of China

AbstractAimOnline species distribution data, global or regional, are increasingly used in biodiversity studies although data limitations have been reported. We explore, for the two major databanks in our research region, how incomplete data are at a large taxonomic and geographic scale, how it is affected by spatial grain, and to what degree it affects inference from analyses of richness or turnover and the environment.LocationChina.Major taxa studiedVascular plants.MethodsWe assembled species lists of all vascular plants from the Global Biodiversity Information Facility (GBIF) and the National Specimen Information Infrastructure (NSII) at three spatial scales (national, provincial, county). We determined the completeness of each compilation by comparing the number of species with that from inventory‐based species list (for 28 provinces, 14 counties, and 146 nature reserves within counties). We related richness from each of the data sources (GBIF, NSII, inventory) to environmental variables (temperature, precipitation, elevational range) and compared regression models among the three data sources. We quantified floristic similarity between regions based on the three data sources and related species turnover to geographic and environmental distances.ResultsData incompleteness was prevalent at all spatial grains, but it increased with decreasing grain and it was higher for GBIF than for NSII. At the national scale, GBIF included 64.1% and NSII included 89.4% of true species richness in China. At the county scale these figures dropped to an average of 12.7% for GBIF and 60.0% for NSII. This changed the order and significance of environmental determinants of richness in regression models. The relationship between floristic similarity and geographic or environmental distance was shallower for GBIF and NSII, compared to inventory data. When the GBIF data were supplemented with the NSII data, the data completeness of GBIF increased from 64.1% to 90.8% at the national scale, from 37.2% to 89.0% at the province scale, and from 12.7% to 63.0% at the county scale.Main conclusionsMain specimen‐record databases are incomplete, which has the potential to heavily affect ecological patterns and mechanisms inferred from these data. Biodiversity analyses based on raw species lists from such sources should be viewed with utmost caution.

Improving estimates of environmental change using multilevel regression models of Ellenberg indicator values.

Ellenberg indicator values (EIVs) are a widely used metric in plant ecology comprising a semi‐quantitative description of species’ ecological requirements. Typically, point estimates of mean EIV scores are compared over space or time to infer differences in the environmental conditions structuring plant communities—particularly in resurvey studies where no historical environmental data are available. However, the use of point estimates as a basis for inference does not take into account variance among species EIVs within sampled plots and gives equal weighting to means calculated from plots with differing numbers of species. Traditional methods are also vulnerable to inaccurate estimates where only incomplete species lists are available.We present a set of multilevel (hierarchical) models—fitted with and without group‐level predictors (e.g., habitat type)—to improve precision and accuracy of plot mean EIV scores and to provide more reliable inference on changing environmental conditions over spatial and temporal gradients in resurvey studies. We compare multilevel model performance to GLMMs fitted to point estimates of mean EIVs. We also test the reliability of this method to improve inferences with incomplete species lists in some or all sample plots. Hierarchical modeling led to more accurate and precise estimates of plot‐level differences in mean EIV scores between time‐periods, particularly for datasets with incomplete records of species occurrence. Furthermore, hierarchical models revealed directional environmental change within ecological habitat types, which less precise estimates from GLMMs of raw mean EIVs were inadequate to detect. The ability to compute separate residual variance and adjusted R 2 parameters for plot mean EIVs and temporal differences in plot mean EIVs in multilevel models also allowed us to uncover a prominent role of hydrological differences as a driver of community compositional change in our case study, which traditional use of EIVs would fail to reveal. Assessing environmental change underlying ecological communities is a vital issue in the face of accelerating anthropogenic change. We have demonstrated that multilevel modeling of EIVs allows for a nuanced estimation of such from plant assemblage data changes at local scales and beyond, leading to a better understanding of temporal dynamics of ecosystems. Further, the ability of these methods to perform well with missing data should increase the total set of historical data which can be used to this end.