Intercept Correction Research Articles

An improved canopy interception scheme into biogeochemical model for precise simulation of carbon and water fluxes in subtropical coniferous forest

The process-based Biome-BGC (Biome Biogeochemical Cycles) model is widely used to simulate the fluxes of carbon and water of terrestrial ecosystems. While exhibiting excellent performance in simulating carbon cycle processes, this model provides a relatively simple simulation of the water cycle processes, particularly in canopy interception, which may result in significant errors in evapotranspiration (ET) and soil moisture estimations. This study initially refined the temporal scale of the original Biome-BGC model from a daily scale to an hourly scale, and then incorporated a theoretical interception module into the hourly-scale model for correcting canopy interception algorithm, to enhance the accuracy of hydrological processes simulations. The modified model was tested using the half-hourly observed meteorological and eddy covariance flux data at the Qianyanzhou subtropical coniferous forest site. In comparison with the original daily-scale model, simulations from the hourly-scale model showed better agreement with measurements at Qianyanzhou forest site, with 30.61 % and 40.92 % lower annual average gross primary productivity (GPP) and ET simulations. Although the accuracy of GPP and ET simulations did not show a significant improvement after canopy interception correction, it notably enhanced the accuracy of canopy interception and soil moisture simulations. The canopy interception rates were 55.8 % and 44.1 % for the original daily-scale and hourly-scale model, obviously overstimated compared with canopy correction simulation (31.1 %), leading to a significant underestimation of runoff. The canopy interception and runoff simulations after interception correction were proven relatively more reasonable. Additionally, the coefficient of determination (R2) for measured vs simulated soil water content (SWC) were 0.38, 0.51 and 0.60 for the original daily-scale, hourly-scale, and canopy interception correction simulations respectively, with a notable improvement in accuracy. This study suggested that improvements in temporal scale and canopy interception for process-based biogeochemical model can provide a better understanding of the carbon and water exchanges in response to instantaneous meteorological conditions and support improved water resource management.

Detecting changes in the performance of a clinical machine learning tool over time

Excessive use of blood cultures (BCs) in Emergency Departments (EDs) results in low yields and high contamination rates, associated with increased antibiotic use and unnecessary diagnostics. Our team previously developed and validated a machine learning model to predict BC outcomes and enhance diagnostic stewardship. While the model showed promising initial results, concerns over performance drift due to evolving patient demographics, clinical practices, and outcome rates warrant continual monitoring and evaluation of such models. A real-time evaluation of the model's performance was conducted between October 2021 and September 2022. The model was integrated into Amsterdam UMC's Electronic Health Record system, predicting BC outcomes for all adult patients with BC draws in real time. The model's performance was assessed monthly using metrics including the Area Under the Curve (AUC), Area Under the Precision-Recall Curve (AUPRC), and Brier scores. Statistical Process Control (SPC) charts were used to monitor variation over time. Across 3.035 unique adult patient visits, the model achieved an average AUC of 0.78, AUPRC of 0.41, and a Brier score of 0.10 for predicting the outcome of BCs drawn in the ED. While specific population characteristics changed over time, no statistical points outside the statistical control range were detected in the AUC, AUPRC, and Brier scores, indicating stable model performance. The average BC positivity rate during the study period was 13.4%. Despite significant changes in clinical practice, our BC stewardship tool exhibited stable performance, suggesting its robustness to changing environments. Using SPC charts for various metrics enables simple and effective monitoring of potential performance drift. The assessment of the variation of outcome rates and population changes may guide the specific interventions, such as intercept correction or recalibration, that may be needed to maintain a stable model performance over time. This study suggested no need to recalibrate or correct our BC stewardship tool. No funding to disclose.

An EQ-5D-5L Value Set for Belgium.

ObjectiveThis study aimed to establish a Belgian EQ-5D-5L value set based on the preferences of the adult Belgian general population.MethodsThe most recent EuroQol Valuation Technology (EQ-VT 2.1) protocol for EQ-5D-5L valuation studies was followed. Computer-assisted personal interviews were carried out in a representative sample of the adult Belgian population. Potential respondents were randomly selected from the National Register using a multistage, stratified, cluster sampling with unequal probability design. Each respondent valued 10 or 11 health states using composite time trade-off (cTTO) and 14 health states in seven paired choice tasks using a discrete choice experiment (DCE). Different model specifications were explored and assessed based on logical consistency, goodness of fit, predictive accuracy and theoretical considerations.ResultsA total of 892 respondents were included in the analyses. The sample was representative of the Belgian adult population in terms of age, sex, region of residence, educational attainment, labour market status, self-assessed health status and health-related quality of life (HRQoL). The preferred model specification was a hybrid (DCE and cTTO data combined) multiplicative eight-coefficient model with intercept random effects and correction for heteroskedasticity. Values range from − 0.532 to 1. Loss of HRQoL is highest in the dimension pain/discomfort, closely followed by anxiety/depression.ConclusionsThis study developed a Belgian EQ-5D-5L value set, based on the preferences of the Belgian adult general population. It provides opportunities for future clinical and economic evaluations in healthcare, for the measurement of patient-reported outcomes and for population health assessments.Supplementary InformationThe online version contains supplementary material available at 10.1007/s41669-022-00353-3.

Plasma and Urine Metabolomic Response to an Ultra-Processed Dietary Pattern: A Biomarker Discovery Analysis in a Domiciled Randomized Controlled Crossover Feeding Trial

ObjectivesTo identify metabolomic markers that differed between dietary patterns (DP) that are either high in or void of ultra-processed foods (UPFs) according to NOVA. MethodsA secondary analysis of a randomized, crossover, controlled feeding trial in which 20 domiciled, healthy participants (mean ± SD: 31 ± 7 years, BMI 22 ± 11.6, 50% female) consumed a UPF-DP (80% UPFs) and an unprocessed DP (UN-DP; 0% UPFs) for two weeks with no washout. DPs were matched for energy, macronutrients, total fiber, total sugar, and sodium; presented at 200% of energy requirements; and consumed ad libitum. Metabolite levels were measured in EDTA plasma at the end of each DP (wk 2) and in 24-hr and spot urine at wk 1 and 2, using untargeted liquid chromatography with high resolution/tandem mass spectrometry and annotated using Metabolon’s reference library and authentic standards. Metabolites (n = 1000 plasma, n = 1272 24-hr urine, and n = 1281 spot urine) with <80% missing data and coefficients of variation <30% were assigned minimum detected values, scaled to median of 1, and log2-transformed. Linear mixed models in SAS identified metabolites that differed between UPF-DP and UN-DP adjusted for trial, DP sequence, timepoint, and body weight changes, with a subject-specific random intercept and Benjamini-Hochberg multiple comparison correction. ResultsFor plasma, 183 metabolites differed between UPF-DP and UN-DP at wk 2. For 24-hr urine, 461 metabolites differed between UPF-DP and UN-DP at wk 1 and 2, 68 of which also differed at wk 1 and 2 for spot urine. Twenty metabolites consistently differed between UPF-DP and UN-DP at each timepoint and for each sample type. The sub pathways for these 20 metabolites included glutamate metabolism (n = 1 metabolite); ascorbate and aldarate metabolism (n = 1); benzoate metabolism (n = 2); methionine, cysteine, SAM and taurine metabolism (n = 2); secondary bile acid metabolism (n = 2); fatty acid dicarboxylate (n = 1); and plant-food components (n = 2); 9 could not be annotated. ConclusionsWe identified exogenous and endogenous metabolites, representing a range of metabolic pathways, that consistently differed between a UPF-DP and UN-DP. These candidate biomarkers of UPF intake require investigation in larger samples with dietary data sufficient for NOVA classification. Funding SourcesNCI, NIDDK.

123: SEVERE LYMPHOPENIA ACQUIRED DURING CHEMORADIOTHERAPY FOR ESOPHAGEAL CANCER: INCIDENCE AND EXTERNAL VALIDATION OF A PREDICTION MODEL

Abstract Background and aim The incidence of grade 4 lymphopenia in patients treated with chemoradiotherapy (CRT) according to Chemoradiotherapy for Oesophageal cancer followed by Surgery Study (CROSS) regimen is unclear. The primary aim was to determine the incidence of grade 4 lymphopenia during CROSS for esophageal cancer. Secondary aims were to externally validate a prediction model for grade 4 lymphopenia and compare overall survival between patients with and without grade 4 lymphopenia. Methods Patients who underwent CRT for esophageal cancer between 2014 and 2019 were eligible for inclusion. Patients with a planned radiation dose of 41.4 Gy (CROSS) or 50.4 Gy (‘extended-CROSS’) and concurrent carboplatin and paclitaxel were included. The primary outcome was the incidence of grade 4 lymphopenia during CRT defined according to Common Terminology Criteria for Adverse Events version 5.0 (i.e. lymphocyte count nadir &amp;lt;0.2 μL). The secondary outcome measures were the prediction model’s external performance (i.e. discrimination and calibration). Overall survival for patients with versus without grade 4 lymphopenia was compared using Kaplan–Meier analysis. Results A total of 219 patients were included of whom 176 patients (80%) underwent CROSS and 43 patients (20%) extended-CROSS. The incidence of grade 4 lymphopenia was 11% in CROSS and 33% in extended-CROSS (P &amp;lt; 0.001). External discrimination yielded a c-statistic of 0.80 (95% confidence interval: 0.70–0.89). External calibration of the model was poor in CROSS but fair in extended-CROSS. Adjusted calibration using intercept correction (adjusted for the lower a-priori risk for grade 4 lymphopenia in CROSS) showed fair agreement between the observed and predicted risk for grade 4 lymphopenia. Median overall survival in patients with versus without grade 4 lymphopenia was 12.7 versus 42.5 months (P = 0.045). Conclusion The incidence of grade 4 lymphopenia is significantly higher in esophageal cancer patients receiving extended-CROSS compared to those receiving CROSS. The prediction model demonstrated good external performance in the setting of the CROSS-regimen and could be used to identify patients at high-risk for grade 4 lymphopenia who might be eligible for lymphopenia–mitigating strategies.

Severe lymphopenia acquired during chemoradiotherapy for esophageal cancer: Incidence and external validation of a prediction model

BackgroundThe incidence of grade 4 lymphopenia in patients treated with chemoradiotherapy (CRT) according to Chemoradiotherapy for Oesophageal cancer followed by Surgery Study (CROSS) regimen is unclear. The primary aim was to determine the incidence of grade 4 lymphopenia during CROSS for esophageal cancer. Secondary aims were to externally validate a prediction model for grade 4 lymphopenia and compare overall survival between patients with and without grade 4 lymphopenia. MethodsPatients who underwent CRT for esophageal cancer between 2014 and 2019 were eligible for inclusion. Patients with a planned radiation dose of 41.4 Gy (CROSS) or 50.4 Gy (“extended-CROSS”) and concurrent carboplatin and paclitaxel were included. The primary outcome was the incidence of grade 4 lymphopenia during CRT defined according to Common Terminology Criteria for Adverse Events version 5.0 (i.e. lymphocyte count nadir < 0.2 µL). The secondary outcome measures were the prediction model’s external performance (i.e. discrimination and calibration). Overall survival for patients with versus without grade 4 lymphopenia was compared using Kaplan–Meier analysis. ResultsA total of 219 patients were included of whom 176 patients (80%) underwent CROSS and 43 patients (20%) extended-CROSS. The incidence of grade 4 lymphopenia was 11% in CROSS and 33% in extended-CROSS (p < 0.001). External discrimination yielded a c-statistic of 0.80 (95% confidence interval: 0.70–0.89). External calibration of the model was poor in CROSS but fair in extended-CROSS. Adjusted calibration using intercept correction (adjusted for the lower a-priori risk for grade 4 lymphopenia in CROSS) showed fair agreement between the observed and predicted risk for grade 4 lymphopenia. Median overall survival in patients with versus without grade 4 lymphopenia was 12.7 versus 42.5 months (p = 0.045). ConclusionThe incidence of grade 4 lymphopenia is significantly higher in esophageal cancer patients receiving extended-CROSS compared to those receiving CROSS. The prediction model demonstrated good external performance in the setting of the CROSS-regimen and could be used to identify patients at high-risk for grade 4 lymphopenia who might be eligible for lymphopenia–mitigating strategies.

Validation study of the ACS NSQIP surgical risk calculator for two procedures in Japan

IntroductionThe ACS NSQIP Surgical Risk Calculator (SRC) assesses risk to support goal-concordant care. While it accurately predicts US outcomes, its performance internationally is unknown. This study evaluates SRC accuracy in predicting mortality following low anterior resection (LAR) and pancreaticoduodenectomy (PD) in NSQIP patients and accuracy retention when applied to native Japanese patients (National Clinical Database, NCD). MethodsNSQIP (41,260 LAR; 15,114 PD) and NCD cases (61,220 LAR; 27,901 PD) from 2015 to 2017 were processed through the SRC mortality model. Country-specific calibration and discrimination were assessed with and without an intercept correction applied to the Japanese data. ResultsThe SRC exhibited acceptable calibration for LAR and PD when applied to NSQIP data but miscalibration for NCD data. A simple correction to the model intercept, motivated by lower mortality rates in the Japanese data, successfully remediated the miscalibration. ConclusionsThe SRC may inaccurately predict surgical risk when applied to the native Japanese population. An intercept correction method is suggested when miscalibration is encountered; it is simple to implement and may permit effective international use of the SRC.

Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed-frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across different models, extending the model specification by adding MA terms, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track using a specific form of intercept correction. Among these methods, adjusting the original nowcasts and forecasts by an amount similar to the nowcast and forecast errors made during the financial crisis and subsequent recovery seems to produce the best results for the US, notwithstanding the different source and characteristics of the financial crisis. In particular, the adjusted growth nowcasts for 2020Q1 get closer to the actual value, and the adjusted forecasts based on alternative indicators become much more similar, all unfortunately indicating a much slower recovery than without adjustment, and very persistent negative effects on trend growth. Similar findings also emerge for forecasts by institutions, for survey forecasts, and for the other G7 countries.

How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

Loss-on-ignition (LOI) is the most widely used measure of organic matter in lake sediments, a variable related to both climate and land-use change. The main drawback for conventional measurement methods is the processing time and hence high labor costs associated with high-resolution analyses. On the other hand, broad-based near infrared reflectance spectroscopy (NIRS) is a time and cost efficient method to measure organic carbon and organic matter content in lacustrine sediments once predictive methods are developed. NIRS-based predictive models are most robust when applied to sediments with properties that are already included in the calibration dataset. To test the potential for a broad applicability of NIRS models in samples foreign to the calibration model using linear corrections, sediment cores from six lakes (537 samples, LOI range 1.03–85%) were used as reference samples to develop a predictive model. The applicability of the model was assessed by sequentially removing one lake from the reference dataset, developing a new model and then validating it against the removed lake. Results indicated that NIRS has a high predictive power (RMSEP < 4.79) for LOI with the need for intercept and slope correction for new cores measured by NIRS. For studies involving many samples, NIRS is a cost and time-efficient method to estimate LOI on a range of lake sediments with only linear bias adjustments for different records.

Forecasting the Covid-19 Recession and Recovery: Lessons from the Financial Crisis

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across different models, extending the model specification by adding MA terms, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track by a specific form of intercept correction. Among all these methods, adjusting the original nowcasts and forecasts by an amount similar to the nowcast and forecast errors made during the financial crisis and following recovery seems to produce the best results for the US, notwithstanding the different source and characteristics of the financial crisis. In particular, the adjusted growth nowcasts for 2020Q1 get closer to the actual value, and the adjusted forecasts based on alternative indicators become much more similar, all unfortunately indicating a much slower recovery than without adjustment and very persistent negative effects on trend growth. Similar findings emerge also for the other G7 countries.

Learning from Errors While Forecasting Inflation: A Case for Intercept Correction

Structural changes are quite common in macroeconomic time series. Internal/external shock(s) may cause significant structural change in any economy. Simplest form of such change is observed as shift in constant of an underlying relationship between a pair of macroeconomic variables. Forecasting from such a model assuming no structural break is tantamount to ignoring the important aspects of underlying economy and mostly results in forecast failure. Intercept correction (adjustment for the realized forecast error) is a method for accommodating such ignored structural break(s). We use a simple model to forecast inflation (based upon single lag of money supply growth) for 25 countries and compare its performance with a) the same model with optimal intercept correction, b) the same model with half intercept correction, and c) a random walk model (with drift). Optimal intercept correction approach outperforms in forecasting next period inflation compared to one from a) the same model without intercept correction, b) the same model with half intercept correction, and c) random walk model. We also observe that higher correction is needed for countries with more volatile inflation.

Characterisation of scintillator-based gamma spectrometers for determination of sample dose rate in OSL dating applications

A recent inter-comparison (Murray et al., 2015) has helped to highlight variability in the measurement of dose rate between luminescence laboratories. Part of this variability probably reflects the difficulties of homogenising and dissolving samples so that the <500 mg used in e.g. ICP-MS and NAA is representative. High resolution gamma spectrometry is the obvious alternative because it can measure samples 100–1000 times larger, but the instrumentation is low-throughput, high capital and running cost, and requires skilled personnel to maintain operation over many years. Here we investigate the potential of traditional low-cost, low maintenance alternatives based on a 3” × 3” NaI(Tl) scintillation crystal. The temperature stability is investigated, and a linear (with intercept) correction for spectra drift based on the 1.46 MeV peak from 40K and the ∼100 keV composite X-ray peak from uranium and thorium is shown to minimise this problem. Using a calibration based on wax impregnated standards, the minimum detection limits (MDL) are 25 Bq/kg (40K), 4.8 Bq/kg (238U), 2.5 Bq/kg (232Th) for 250–300 g of sample; systematic deviations around the expected values are also shown to be acceptable as the MDL is approached. Finally, we compare the activity concentrations and resulting dry dose rates derived from our NaI-based system with those from routine high resolution gamma spectrometry, and conclude that the new analytical facility is very suitable for accurate and precise dose rate determination.

Evaluation of anal fin spines, otoliths, and scales for estimating age and back-calculated lengths of yellow perch in southern Green Bay

Abstract Southern Green Bay supports important fisheries for yellow perch Perca flavescens and valid estimates of age structure and growth are critical to effective management. Anal fin spines and scales are used by the Wisconsin Department of Natural Resources for age estimation, but these structures may provide lower precision and accuracy than otoliths. The primary objective of our assessment was to determine if age estimates, among-reader precision, and mean back-calculated total lengths (TLs) at age differed among scales, anal fin spines, and otoliths. Ages estimated from anal fin spines were more precise than scale ages, were as precise as otolith-based ages, and generally agreed with consensus ages estimated from sectioned otoliths. Relationships between TL and radii of calcified structures were linear for scales, anal spines, and otoliths along two different transects. Mean back-calculated TLs were generally similar between intercept-corrected direct proportion (ICDP) and linear regression (LR) models, but otolith-based direct proportion models (no intercept correction) generally provided higher back-calculated mean TLs at ages 1 and 2 than ICDP and LR models. Mean back-calculated TLs at age estimated from whole otoliths were higher than estimates for other structures; but differences among anal fin spines, scales, and sectioned otoliths were

Trends in atmospheric evaporative demand in Great Britain using high-resolution meteorological data

Abstract. Observations of climate are often available on very different spatial scales from observations of the natural environments and resources that are affected by climate change. In order to help bridge the gap between these scales using modelling, a new dataset of daily meteorological variables was created at 1 km resolution over Great Britain for the years 1961–2012, by interpolating coarser resolution climate data and including the effects of local topography. These variables were used to calculate atmospheric evaporative demand (AED) at the same spatial and temporal resolution. Two functions that represent AED were chosen: one is a standard form of potential evapotranspiration (PET) and the other is a derived PET measure used by hydrologists that includes the effect of water intercepted by the canopy (PETI). Temporal trends in these functions were calculated, with PET found to be increasing in all regions, and at an overall rate of 0.021 ± 0.021 mm day−1 decade−1 in Great Britain. PETI was found to be increasing at a rate of 0.019 ± 0.020 mm day−1 decade−1 in Great Britain, but this was not statistically significant. However, there was a trend in PETI in England of 0.023 ± 0.023 mm day−1 decade−1. The trends were found to vary by season, with spring PET increasing by 0.043 ± 0.019 mm day−1 decade−1 (0.038 ± 0.018 mm day−1 decade−1 when the interception correction is included) in Great Britain, while there is no statistically significant trend in other seasons. The trends were attributed analytically to trends in the climate variables; the overall positive trend was predominantly driven by rising air temperature, although rising specific humidity had a negative effect on the trend. Recasting the analysis in terms of relative humidity revealed that the overall effect is that falling relative humidity causes the PET to rise. Increasing downward short- and longwave radiation made an overall positive contribution to the PET trend, while decreasing wind speed made a negative contribution to the trend in PET. The trend in spring PET was particularly strong due to a strong decrease in relative humidity and increase in downward shortwave radiation in the spring.

Exploring the use of NIR reflectance spectroscopy in prediction of free L-Asparagine in solanaceae plants

Much researches of Near-infrared spectroscopy modeling methods that are utilized to analyze the trace amount components, especially indirect modeling on complex system, have gained widely attraction in recent years. Amino acids in plants are essential nutrients of maintaining growth and ensuring health. As the important participants in various biochemical reactions in plants, nondestructive detection of free amino acids will provide meaningful observation on physiological changing in different steps of plant growth. In this research, two hundred and twenty-two samples were measured to obtain the concentration of free L-Asparagine in plant by amino acid analyzer. NIR spectra were also collected for conducting chemometrics modeling. Different spectral pretreatments and variables selecting methods were employed to optimize the NIR models. Independent validation set as well as unknown samples from different years were successfully predicted by using the slope intercept correction. Results in this study demonstrated that fast analysis of free L-Asparagine can be established by NIR modeling approach.

Prevalence of Malocclusion among 10-12-year-old Schoolchildren in Kozhikode District, Kerala: An Epidemiological Study.

ABSTRACTBackground: A malocclusion is an irregularity of the teeth or a malrelationship of the dental arches beyond the range of what is accepted as normal.Objectives: To determine the prevalence of malocclusion in children aged 10-12 years in Kozhikode district of Kerala, South India.Materials and methods: A descriptive cross-sectional study was conducted among schoolchildren aged 10-12 years in six schools in Kozhikode district of Kerala, South India. A total of 2,366 children satisfied the inclusion criteria. Occlusal characteristics like crossbite, open bite, deep bite, protrusion of teeth, midline deviations, midline diastema and tooth rotation were recorded. The data were tabulated and analyzed using Chi-square test.Results: The results revealed that the overall prevalence of malocclusion was 83.3%. Of this, 69.8% of the children had Angle’s class I malocclusion, 9.3% had class II malocclusion (division 1 = 8.85%, division 2 = 0.5%) and 4.1% had class III malocclusion; 23.2% showed an increased overjet (>3 mm), 0.4% reverse overjet, 35.6% increased overbite (>3 mm), 0.29% open bite, 7.2% crossbite with 4.6% crossbite of complete anterior teeth, 63.3% deviation of midline, 0.76% midline diastema and 3.25% rotated tooth. No significant differences in gender distributions of malocclusions were noted except for increased overjet and overbite.Conclusion: There is high prevalence of malocclusion among schoolchildren in Kozhikode district of Kerala. Early interception and early correction of these malocclusions will eliminate the potential irregularities and malpositions in the developing dentofacial complex.How to cite this article: Narayanan RK, Jeseem MT, Kumar TVA. Prevalence of Malocclusion among 10-12-year-old Schoolchildren in Kozhikode District, Kerala: An Epidemiological Study. Int J Clin Pediatr Dent 2016;9(1):50-55.

Multistep forecasting in the presence of location shifts

This paper studies the properties of iterated and direct multistep forecasting techniques in the presence of in-sample location shifts (breaks in the mean). It also considers the interactions of these techniques with multistep intercept corrections that are designed to exhibit robustness to such shifts. In a local-asymptotic parameterization of the probability of breaks, we provide analytical expressions for forecast biases and mean-square forecast errors. We also provide simulations which show that breaks provide a rationale for using methods other than iterated multistep techniques. In particular, we study the relationships between the relative accuracy of the methods and the forecast horizon, the sample size and the timing of the shifts. We show that direct multistep forecasting provides forecasts that are relatively robust to breaks, and that its benefits increase with the forecast horizon. In an empirical application, we revisit an oft-used dataset of G7 macroeconomic series and corroborate our theoretical results.

Beating the VAR: Improving Swedish GDP Forecasts Using Error and Intercept Corrections

This paper examines the forecast accuracy of an unrestricted vector autoregressive (VAR) model for GDP, relative to a comparable vector error correction model (VECM) that recognizes that the data are characterized by co‐integration. In addition, an alternative forecast method, intercept correction, is considered for further comparison. Recursive out‐of‐sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VECM consistently outperforms the VAR models. Further, intercept correction enhances the forecast accuracy when applied to the VECM, whereas there is no such indication when applied to the VAR model. For certain forecast horizons there is a significant difference in forecast ability between the intercept corrected VECM compared to the VAR model. Copyright © 2015 John Wiley &amp; Sons, Ltd.

A Single Versatile Appliance for Habit Interception and Crossbite Correction.

Digit sucking is a common childhood behavior, which has an adaptive value for children up to the fourth year of life. It is usually associated with oral pleasure and self-comforting behavior. But chronic practice may produce deleterious effect in the form of dental and skeletal deformities. Adjunctive therapy using bluegrass appliance as a permanent reminder and quadhelix appliance as a reminder as well as a slow palatal expander has proven successful in intercepting digit-sucking habit and expanding the arch for crossbite correction. In the present case, a versatile modified quadhelix appliance incorporating a roller was designed to clinically correct the habit and its resulting dentofacial deformities.

Model selection in under-specified equations facing breaks

When a model under-specifies the data generation process, model selection can improve over estimating a prior specification, especially if location shifts occur. Impulse-indicator saturation (IIS) can ‘correct’ non-constant intercepts induced by location shifts in omitted variables, which leave slope parameters unaltered even when correlated with included variables. Location shifts in included variables induce changes in estimated slopes when there are correlated omitted variables. IIS helps mitigate the adverse impacts of induced location shifts on non-constant intercepts and estimated standard errors, and can provide an automatic intercept correction to improve forecasts following location shifts.