Average Treatment Effect Research Articles

Does the European Union Start-Up Aid Help Young Farmers to Innovate and to Join Networks?

The endurance and vitality of European agriculture are threatened by the aging of farmers, together with the lack of generational change. The small share of young farmers also impacts on the innovative capacity and competitiveness of the sector. The Common Agricultural Policy of the European Union started addressing the issue long ago by providing financial aid to help young farmers to start up. Over time, the aid increased and packages of measures were set to reinforce the aid and to promote investments, innovations, and networks at the farm level. While the literature focuses on analyzing the effectiveness of the start-up aid in fostering new entries, this paper assumes an original perspective as it seeks to assess whether this aid has actually promoted innovations and networks in the beneficiary farms. The analysis relies on sample data collected in 2021 in Italy and Poland via interviews of 500 farmers under 40 who had entered the sector both with and without the aid. A probit model estimates whether the beneficiaries have a higher probability to innovate and network. Then, the contribution of the aid to the intensity of the adoption of innovations and networks is estimated via an Average Treatment Effect on the Treated model (ATT). Results suggest that the start-up aid increased the adoption of innovations and networks. The ATT indicates that this positive effect holds even after correcting for self-selection bias. By adopting an original perspective, our analysis suggests that the start-up aid for young farmers goes beyond rejuvenating agriculture by fostering innovation at the farm level and by promoting networking, thus enhancing agricultural change. However, farmer behaviors in the two countries are different, suggesting quite complex patterns for the impact of this measure.

Effect of a small increase in off-premises trading hours on alcohol sales in Norway: A stepped-wedge cluster-randomized controlled trial.

Evidence of the effect of limiting off-premises alcohol trading hours is still scarce. This study tested the effect of a small extension in trading hours on alcohol sales in alcohol monopoly outlets in Norway. The extension of trading hours was implemented within a stepped-wedge cluster-randomized trial design. Eligible state monopoly outlets (n = 229) were clustered into trade districts (n = 62), which were block-randomized to one of three sequences regarding date of implementation: 1 September 2020 (n = 21 districts, 82 outlets), 1 December 2020 (n = 21 districts, 73 outlets) and 1 March 2021 (n = 20 districts, 74 outlets). Outcomes were followed-up for a 1-year period. Study participants were state monopoly outlets in urban and rural trade districts in all parts of Norway. Monthly alcohol sales in litres of pure alcohol per trade district and per outlet were measured from March 2020 to March 2022 (primary outcome). We applied a linear mixed-effect model with two-way fixed effects within a difference-in-difference framework. As a robustness check we considered the effects of cross-border trade and effects in subgroups of outlets. Trading hours in monopoly outlets were extended by 1 hour on Saturdays. The extension was permanent. Pre-intervention periods and not-yet-treated units served as control conditions. We did not find a statistically significant effect of the small extension in trading hours on monthly alcohol sales (i) per trade district [average treatment effect: -185.5litres, 95% confidence interval (CI) = -1159.9, 788.9] and (ii) per outlet (-35.3litres, 95% CI = -142.1, 72.0). These findings were consistent across estimation methods and model specifications. There is no clear evidence that a small extension in off-premises trading hours affected alcohol sales in monopoly outlets in Norway.

Long-term health outcomes of young patients with low-complexity coronary disease: a weighted analysis according to revascularization strategy.

Age is an important factor weighing on revascularization decisions. We analysed long-term health outcomes of young patients with low-complexity coronary anatomy suitable for both coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI), according to revascularization strategy. Patients 60 years old or less, undergoing invasive coronary angiography between January 2007 and December 2015, presenting with proximal left anterior descending artery involvement, left main or multivessel disease and a SYNTAX Score ≤22 were retrospectively selected. An inverse probability of treatment weight methodology generated a pseudopopulation with well-balanced characteristics, which was used to estimate the average treatment effect between PCI (n = 374) and CABG (n = 173). Mean age was 53 ± 7 years old, 27% had diabetes mellitus and 48% presented with an acute coronary syndrome. Mean SYNTAX score was 13.6 ± 4.9 and 68% underwent PCI as index revascularization strategy. In the weighed population, the adjusted hazard of the primary end-point of all-cause death at total follow-up (median 9.3 years; interquartile range 6.9-11.7) was 0.40 (95% confidence interval 0.19-0.7) for CABG vs PCI (incidence rate 5.8 vs 14.0 deaths/1000-person-years). Accounting for death as competing risk, the cumulative hazard of new revascularization (sub-distribution hazard ratio 0.72; 95% confidence interval 0.32-1.25) and any cause hospital readmission (sub-distribution hazard ratio 0.70; 95% confidence interval 0.41-1.07) were lower in CABG patients, as opposed to death/stroke rates at 30 days which were higher with CABG (0.3% vs 1.7%; risk ratio = 5.84). In this quasi-experimental analysis of young patients with coronary artery disease and an equivalent indication for both PCI and CABG, long-term health outcomes were favourably associated with CABG, as compared to PCI. These observations support the need for dedicated randomized trials with longer follow-up in order to better inform lifetime treatment options.

Are Cooked Nutritious School Lunches Associated with Improved Attendance? Findings from the 2022-2023 Tasmanian School Lunch Project.

Background/Objectives: During 2022-2023, the School Lunch Project (SLP) provided free nutritious cooked lunches 1-4 days per week to Kinder to Grade 10 students attending 30 schools in areas of high disadvantage in Tasmania, Australia. This analysis examined if the SLP was associated with student attendance. Methods: Staff (teachers, support staff, and principals) from 12 schools completed an online survey and/or participated in focus groups/interviews. Government-held, objectively measured, grade-level attendance data were provided for 17 SLP and 11 matched comparison schools for 2018-2023. Linear mixed models compared attendance on school lunch and non-school lunch days in SLP schools. Difference-in-difference regression compared attendance between SLP and comparison schools. Qualitative data were analysed thematically. Results: Sixty-five staff completed surveys, where 22% reported that increased attendance was a benefit of the SLP. Similar findings were observed in the staff focus groups/interviews (N = 51). Mean attendance was similar on school lunch and non-school lunch days among the SLP schools during 2022 (difference: 0.04, 95% CI: -0.5, 0.6) and 2023 (difference 0.1, 95% CI: -0.2, 0.4) and similar between SLP and comparison schools (average treatment effect in the treated: 1.2, 95% CI: -0.7, 3.0). Conclusions: The SLP was perceived by some staff to improve attendance but was not associated with objectively measured attendance examined at the grade level.

Early childhood intervention and children's health development : Exemplary findings and methodological challenges in the use of the school entry examination

Early childhood intervention is intended to systematically network and customise support services, particularly for socio-economically disadvantaged families. The programmes are universal or selective, but the evidence on their effectiveness is limited. The aims of this study were to exemplary analyse whether participants in early childhood intervention services had better development than non-participants using the school entry examination (SEE) as well as to discuss to what extent the SEE can be used to assess the impact of early childhood intervention services. We analysed three typical offers of early childhood intervention services (family education; Zukunft für Kinder (ZfK); Kita-U) in relation to full vaccination coverage and age-appropriate development at U9. Data from 4579 Düsseldorf first graders were included. Propensity score matching was used to calculate percentage differences (average treatment effect on the treated; ATT) in terms of immunisation coverage and development between comparable intervention and control groups. All programmes are associated with aslightly increased probability of full vaccination protection (ATT2.1 for family education; 2.5 for ZfK; 5.3 for Kita-U). Family education is also associated with aslightly higher probability of age-appropriate development (ATT 1.6), while the probability of age-appropriate development is lower for participants in ZfK (-10.1) and Kita‑U (-4.5). The evaluation of early childhood intervention, especially selective services, is amethodological challenge due to confounding and suitable comparison groups. However, the SEE could be aframework for impact analyses under specific conditions.

Lung ultrasound assessment of atelectasis following different anesthesia induction techniques in pediatric patients: a propensity score-matched, observational study

IntroductionAtelectasis is a well-documented complication in pediatric patients undergoing general anesthesia. Its incidence varies significantly based on surgical procedures and anesthesia techniques. Inhalation induction, commonly used to avoid the discomfort of venipuncture, is suspected to cause higher rates of respiratory complications, including atelectasis, compared to intravenous induction. This study aimed to evaluate the impact of inhalation versus intravenous anesthesia induction on atelectasis formation in pediatric patients, as assessed by lung ultrasound (LUS).MethodsThis propensity score-matched observational study was conducted at a tertiary pediatric hospital in Milan, Italy. Inclusion criteria were children ≤ 18 years undergoing elective surgery with general anesthesia. Patients were divided into inhalation and intravenous induction groups. LUS was performed before and after anesthesia induction to assess lung aeration. The primary endpoint was the global LUS score post-induction, with secondary endpoints including the incidence and distribution of atelectasis.ResultsOf the 326 patients included, 65% underwent inhalation induction and 35% intravenous induction. The global LUS score was significantly higher in the inhalation group (12.0 vs. 4.0, p < 0.001). After propensity score matching (for age, presence of upper respiratory tract infection, duration of induction, and PEEP levels at induction), average treatment effect (ATE) of mask induction was 5.89 (95% CI, 3.21–8.58; p < 0.001) point on LUS global score and a coefficient of 0.35 (OR 1.41) for atelectasis.DiscussionInhalation induction is associated with a higher incidence of atelectasis in pediatric patients also when we adjusted for clinically relevant covariates.Trial registrationClinicalTrials.gov identifier: NCT06069414.

Impact of Antibiotic Choice at the Time of Sacral Neuromodulation Implantation on Rates of Surgical Site Infection.

To evaluate the efficacy of specific antibiotic regimens in preventing infection following sacral neuromodulation. This is a retrospective cohort study utilizing the Premier Healthcare Database. Patients who underwent sacral neuromodulation placement between January 2016 and March 2020. The patients were grouped by those who received dual antibiotic therapy per 2019 AUA guidelines (Gram positive + broad Gram negative coverage), first- or second-generation cephalosporins or any other regimen. Comparison between groups was performed using Kruskal-Wallis and χ2 tests for continuous and categorical variables, respectively. Inverse probability of treatment weighted (IPTW) analysis was used to estimate the average treatment effect of AUA guidelines regimens versus the use the first- or second-generation cephalosporins alone. The sample included 14 179 patients, with 2211 patients receiving prophylaxis that followed the AUA guideline recommendations. There was no significant difference in surgical site infection rates within 3 months (p = 0.28) or within 12 months (p = 0.53) between the groups. On IPTW, the probability of an infection at 3 months was lower with the AUA guideline regimens compared to those who received first- or second-generation cephalosporins alone, but this difference was not statistically significant (OR = 0.73, 95% CI: [0.43, 1.24]). In the absence of allergies to cephalosporins or penicillin, first- or second-generation cephalosporins alone may be a sufficient preoperative antibiotic regimen for prevention of infection at the time of sacral neuromodulation. Not applicable due to being a database study.

A causal inference framework for leveraging external controls in hybrid trials.

We consider the challenges associated with causal inference in settings where data from a randomized trial are augmented with control data from an external source to improve efficiency in estimating the average treatment effect (ATE). This question is motivated by the SUNFISH trial, which investigated the effect of risdiplam on motor function in patients with spinal muscular atrophy. While the original analysis used only data generated by the trial, we explore an alternative analysis incorporating external controls from the placebo arm of a historical trial. We cast the setting into a formal causal inference framework and show how these designs are characterized by a lack of full randomization to treatment and heightened dependency on modeling. To address this, we outline sufficient causal assumptions about the exchangeability between the internal and external controls to identify the ATE and establish a connection with novel graphical criteria. Furthermore, we propose estimators, review efficiency bounds, develop an approach for efficient doubly robust estimation even when unknown nuisance models are estimated with flexible machine learning methods, suggest model diagnostics, and demonstrate finite-sample performance of the methods through a simulation study. The ideas and methods are illustrated through their application to the SUNFISH trial, where we find that external controls can increase the efficiency of treatment effect estimation.

The Ambulatory Diabetes Outreach Program (ADOP): Rigorous Evaluation of a Pharmacist and Nurse-Led Care Model.

Although several systematic reviews found that ambulatory diabetes mellitus (DM) interventions involving pharmacists generally yielded better outcomes than the ones that did not, existing studies have limitations in rigor and study design. To examine the intention-to-treat effects of the Ambulatory Diabetes Outreach Program (ADOP) on participants' A1c values and healthcare utilization over a 52-month follow-up period. Difference-in-differences with staggered adoption. Specifically, we employed the Callaway and Sant'Anna's "group-time average treatment effect" estimator using not-yet treated as controls adjusting for patient's age, BMI, sex, race, comorbidity, payor, and socio-economic status. All patients with at least one ADOP treatment encounter from July 2017 to October 2021, regardless of program completion or length of exposure to the program. ADOP, a collaborative population health program led by pharmacists and nurse specialists to provide individualized type 2 DM management and education within a large and diverse health system. Patients' A1c values and healthcare utilization, including inpatient admission, inpatient days, and numbers of visits to the emergency department, urgent care, and primary care in recent 6months. ADOP participation was associated with an overall average reduction of 1.04 percentage points (95%CI - 1.12, - 0.95) in A1c level. Similar A1c reductions were also observed in the subgroups by sex and race/ethnicity. An average of 2months were required to reach the overall average effect, which persisted over 4years. Compared to the respective utilization levels pre-intervention, participants also had average reductions in inpatient admissions by 32.4%, inpatient days by 81.6%, visits to the emergency department by 21.6%, and primary care by 17.9%. The results suggest that a collaborative model of pharmacist and nurse-led type 2 DM intervention was effective in improving A1c outcomes and reducing healthcare utilization in the long term.

Access to credit and scale efficiency: Evidence from family farms in East China

Productivity improvement is an important driving force for developing countries to accelerate the development of agricultural sectors and promote the transformation of economic structures. However, few studies have focused on the impact of credit access on family farms’ scale efficiency, a contributor to productivity changes. We address this gap by using data collected from a survey of 565 family farms in East China. The stochastic frontier input distance function (SFIDF) is utilized to measure the scale efficiency, and the endogenous switching regression model (ESRM) is employed to estimate average treatment effect (ATT) and address the selection bias. The empirical results show that the average scale efficiency is 0.768, with credit users and non-users averaging 0.802 and 0.737, respectively. Most family farms operate below their optimal production scale, and only about 14.5% of family farms exceed this optimal scale. Access to credit has significantly improved the scale efficiency of family farms and has not contributed to the excessive pursuit of scale expansion for financial subsidies. These findings are validated by robustness checks. The conclusions of our study have important implications for developing countries seeking to increase financial support for agricultural development.

Primary care payment models and avoidable hospitalizations in Ontario, Canada: A multivalued treatment effects analysis.

Improving access to primary care physicians' services may help reduce hospitalizations due to Ambulatory Care Sensitive Conditions (ACSCs). Ontario, Canada's most populous province, introduced blended payment models for primary care physicians in the early- to mid-2000s to increase access to primary care, preventive care, and better chronic disease management. We study the impact of payment models on avoidable hospitalizations due to two incentivized ACSCs (diabetes and congestive heart failure) and two non-incentivized ACSCs (angina and asthma). The data for our study came from health administrative data on practicing primary care physicians in Ontario between 2006 and 2015. We employ a two-stage estimation strategy on a balanced panel of 3710 primary care physicians (1158 blended-fee-for-service (FFS), 1388 blended-capitation models, and 1164 interprofessional team-based practices). First, we account for the differences in physician practices using a generalized propensity score based on a multinomial logit regression model, corresponding to three primary care payment models. Second, we use fractional regression models to estimate the average treatment effects on the treated outcome (i.e., avoidable hospitalizations). The capitation-based model sometimes increases avoidable hospitalizations due to angina (by 7 per 100,000 patients) and congestive heart failure (40 per 100,000) relative to the blended-FFS-based model. Switching capitation physicians into interprofessional teams mitigates this effect, reducing avoidable hospitalizations from congestive heart failure by 30 per 100,000 patients and suggesting better access to primary care and chronic disease management in team-based practices.

Comparison of Hospital Stay After Open Abdominal Aortic Aneurysm Repair With or Without Enhanced Recovery Protocol

ObjectiveEnhanced recovery after surgery (ERAS) is a protocol of evidence based practices applied in major surgery. Open aortic aneurysm repair is major surgery in terms of complications and mortality. This study aimed to compare early outcomes of ERAS with a traditional post-operative protocol in patients undergoing elective open aortic surgery. MethodsThis retrospective cohort study was conducted between 2018 – 2022 in two tertiary vascular surgery centres. The ERAS program was routinely implemented in one centre, while the other one used a standard peri-operative protocol. The primary outcome was post-operative length of stay (pLOS). Secondary outcomes were 30 day mortality, complications, re-interventions, and rehospitalisations. Propensity score weighting was used to balance the two groups by comorbidities. Inverse probability of treatment weight (IPTW) was used to estimate the average treatment effect on the treated patients. ResultsA total of 198 patients were enrolled: 128 in the ERAS group (EG) and 70 in the standard group (SG). Mean age was 70.8 ± 6.7 years in EG and 71.1 ± 6.7 in SG (p = .34). No significant differences were observed in pre-operative cardiovascular risk factors. Median pLOS was 5 days (IQR 3, 6) in the EG group and 8 days (IQR 6, 11) in the SG group (p < .001). No differences in terms of mortality, re-operations, and rehospitalisations were observed. The IPTW analyses showed a 40% reduction in pLOS and a significant reduction in major complications in EG (OR 0.41, 95% CI 0.26 – 0.66; p < .001). A 45% increase in pLOS in patients with chronic obstructive pulmonary disease was found in both groups. ConclusionEnhanced recovery after surgery is safe and feasible for elective open aortic surgery, and associated with earlier hospital discharge without differences in terms of mortality and lower complication rates compared with a standard protocol. Chronic obstructive pulmonary disease is a major risk factor for an increase in pLOS. The ERAS protocol is promising in terms of resource utilisation.

Beyond half-mile circle: Measuring the impact of subway expansion on home-based travels in Beijing, China

Subways play an important role in supporting travel needs, yet whether the benefits of subway expansion can justify the substantial investments remains a much-debated question. Existing studies have arbitrarily defined the catchment area of a subway station using walking distance and have disproportionately focused on commuting trips, potentially underestimating broader subway effects. To address these limitations, this study employed the distance-band approach to accurately define the treatment area of subway stations while incorporating both local and network effects. Based on longitudinal mobile signaling data, we used the difference-in-differences approach to estimate the average treatment effects of 32 new subway stations on different types of home-based travels in Beijing, China. We found that the opening of new subway stations has led to significant increases in subway usage, trip duration, and trip distance within a 2000-metre radius, and that commuting trips have been more affected than home-based non-commuting trips, except during the COVID-19 pandemic. Moreover, the new subway stations also enhanced the connectivity of the city-wide network, influencing the travel behavior of residents in the vicinity of existing subway stations. We further found that subway expansion is particularly beneficial for women, younger residents, and residents of low-rent neighborhoods. According to these findings, planning new subway stations in Beijing and other densely populated megacities requires an integrated approach that considers the relationships between the existing transport network and diverse travel demand.

Effect of Studying Abroad on Catch-Up Vaccination in Young Adults: A Study Using the Japan Pretravel Consultation Registry1

PurposeTo investigate the effect of studying abroad on catch-up vaccination coverage for measles, rubella, mumps, varicella, and tetanus during the pretravel consultation among young adult travelers. MethodsThis retrospective cohort study analyzed data from the Japan Pretravel Consultation Registry (J-PRECOR) on individuals aged 18–21 years with childhood vaccination records. Propensity score weighting was used to estimate the average treatment effect on the proportion of participants receiving catch-up vaccination. ResultsAmong 1,091 eligible participants, the catch-up vaccination need was highest for mumps (65.7%) and varicella (49.0%) and lowest for measles (9.9%) and rubella (14.0%). In the unadjusted analysis, the catch-up vaccination rate was 70.6% for tetanus, 50.9% for measles, 47.7% for rubella, 40.0% for mumps, and 23.9% for varicella. In the weighted analysis, the study-abroad group had significantly higher catch-up vaccination rates for measles (54.6% vs. 29.8%, P = 0.039), rubella (53.0% vs. 22.1%, P < 0.001), and varicella (26.8% vs. 10.9%, P = 0.002), whereas the non-study-abroad group had a higher catch-up vaccination rate for tetanus (62.4% vs. 78.4%, P = 0.024). ConclusionCompared with other travelers, the catch-up vaccination rate among travelers studying abroad was higher for measles, rubella, and varicella, but lower for tetanus. In clients planning to study abroad, vaccinations required for travel should be recommended in addition to those required by the host institution, and vaccination against highly infectious diseases with potential for complications, such as measles, rubella, mumps, and varicella, should be recommended to clients traveling for reasons other than studying abroad.

Comparative Effectiveness of Anti-Hyperlipidemic Drugs Monotherapy in Primary Prevention of Cardiovascular Disease.

Anti-hyperlipidemic drug treatments are effective in reducing the risk of cardiovascular disease. In a long-term retrospective inception cohort study, we aimed to assess the real-world comparative effectiveness of anti-hyperlipidemic monotherapies for primary prevention of cardiovascular events. Patients aged 18 years and older, who initiated primary prevention with anti-hyperlipidemic monotherapy, were selected from the University of Groningen IADB.nl dispensing database. In intention-to-treat (ITT) analysis we included all patients, whereas in per-protocol (PP) analysis we included both all patients independent of adherence (PPIA) and adherent patients (PPA). Study outcome was the time to first prescription of acute cardiac drug therapy measured by valid drug proxies to identify a first major cardiovascular event. We applied inverse probability of treatment-weighted (IPTW) analysis using Cox regression and time-varying Cox regression with simvastatin as the reference category to estimate the average treatment effect hazard ratios (HR) and their corresponding 95% confidence intervals (CI). Atorvastatin users had significantly higher hazards compared to simvastatin users (HR range: 1.27 to 1.47, 95% CI: 1.15 to 1.69). Similarly, Pravastatin users also exhibited increased hazards compared to simvastatin users (HR range: 1.41 to 1.56, 95% CI: 1.14 to 2.04). Similar patterns were observed in patients with diabetes, rheumatoid arthritis, and asthma/COPD. No differences were found in the hazards of rosuvastatin, fluvastatin, fibrates, and simvastatin. Atorvastatin and pravastatin users had higher long-term rates of cardiovascular events compared to simvastatin monotherapy in primary prevention, the difference may be attributed to the confounding by severity, but also possibly due to differences in drug mechanisms or patient response. These findings could influence current guideline recommendations, suggesting a potential preference for simvastatin in primary prevention, underscoring the need for further research to explore long-term impacts and underlying mechanisms, especially in diverse populations.

Does college selectivity reduce obesity? A partial identification approach.

We use data from the National Longitudinal Study of Adolescent to Adult Health to investigate whether the quality of tertiary education -measured by college selectivity-causally affects obesity prevalence in the medium run (by age 24-34) and in the longer run (about 10years later). We use partial identification methods, which allow us, while relying on weak assumptions, to overcome the potential endogeneity of college selectivity as well as the potential violation of the stable unit treatment value assumption due to students interacting with each other, and to obtain informative identification regions for the average treatment effect of college selectivity on obesity. We find that attending a more selective college causally reduces obesity, both in the medium and in the longer run. We provide evidence that the mechanisms through which the impact of college selectivity on obesity operates include an increase in income, a reduction in physical inactivity and in the consumption of fast food and sweetened drinks.

Uncovering individualised treatment effects for educational trials.

Large-scale Randomised Controlled Trials (RCTs) are widely regarded as "the gold standard" for testing the causal effects of school-based interventions. RCTs typically present the statistical significance of the average treatment effect (ATE), which captures the effect an intervention has had on average for a given population. However, key decisions in child health and education are often about individuals who may be very different from those averages. One way to identify heterogeneous treatment effects across different individuals, not captured by the ATE, is to conduct subgroup analyses. For example, free school meal (FSM) pupils as required for projects funded by the Education Endowment Foundation (EEF) in England. These subgroup analyses, as we demonstrate in 48 EEF-funded RCTs involving over 200,000 students, are usually not standardised across studies and offer flexible degrees of freedom to researchers, potentially leading to mixed, if not misleading, results. Here, we develop and deploy an alternative to ATE and subgroup analysis, a machine-learning and regression-based framework to predict individualised treatment effects (ITEs). ITEs could show where an intervention worked, for which individuals, and to what extent. Our findings have implications for decision-makers in fields like education, healthcare, law, and clinical practices concerning children and adolescents.

AteMeVs: An R package for the estimation of the average treatment effect with measurement error and variable selection for confounders.

In causal inference, the estimation of the average treatment effect is often of interest. For example, in cancer research, an interesting question is to assess the effects of the chemotherapy treatment on cancer, with the information of gene expressions taken into account. Two crucial challenges in this analysis involve addressing measurement error in gene expressions and handling noninformative gene expressions. While analytical methods have been developed to address those challenges, no user-friendly computational software packages seem to be available to implement those methods. To close this gap, we develop an R package, called AteMeVs, to estimate the average treatment effect using the inverse-probability-weighting estimation method to handle data with both measurement error and spurious variables. This developed package accommodates the method proposed by Yi and Chen (2023) as a special case, and further extends its application to a broader scope. The usage of the developed R package is illustrated by applying it to analyze a cancer dataset with information of gene expressions.

The impact of Pradhan Mantri Ujjwala Yojana on Indian households

This study critically evaluates the impact of the Pradhan Mantri Ujjwala Yojana (PMUY) on LPG accessibility among poor households in India. Using Propensity Score Matching and Difference-in-Differences estimators and the National Family Health Survey (NFHS) dataset, the Average Treatment Effect on the intendedly Treated is a modest 2.1 percentage point increase in LPG consumption due to PMUY, with a parallel decrease in firewood consumption. Regional analysis reveals differential impacts, with significant progress in the North, West, and South but less pronounced effects in the East and North East. The study also underscores variance across social groups, with Scheduled Caste households showing the most substantial benefits, while Scheduled Tribes households are hardly affected. Despite the PMUY’s initial success in facilitating LPG access, sustaining its usage remains challenging. Policy should emphasise targeted interventions and address regional and community-specific disparities for the sustained usage of LPG.

Pooled analysis of the MANTICO2 and MONET randomized controlled trials comparing drug efficacy for early treatment of COVID-19 during Omicron waves

BackgroundThe clinical effectiveness of early therapies for mild-to-moderate COVID-19, comparing antivirals and monoclonal antibodies (mAbs) during the Omicron era, has not been conclusively assessed through a post-approval comparative trial. We present a pooled analysis of two randomized clinical trials conducted during Omicron waves. Methods The MANTICO2/MONET trial is a pooled analysis of two multicentric, independent, phase-4, three-arm, superiority, randomized, open-label trials. Nonhospitalized patients with early mild-to-moderate COVID-19 (≤5 days after symptoms’ onset) and at least one risk factor for disease progression were randomized 1:1:1 to receive 500mg of intravenous sotrovimab (SOT) or 600mg of intramuscular tixagevimab/cilgavimab (TGM/CGM) or oral 5-days course of nirmatrelvir/ritonavir (NMV/r) 300/100mg BID. Primary outcome was COVID-19-related hospitalization or death within 29 days after randomization. Fisher’s exact test for pooled data and incidence of failure was reported as overall and by arm with respective 95% CI.Pairwise comparisons across the arms were conducted using unadjusted exact logistic regression. An analysis by means of a doubly robust marginal model using augmented inverse probability weighting (AIPW) was also conducted to estimate the potential outcomes (Pom) in each treatment group and their difference by the average treatment effect (ATE). Analysis of symptom persistence within 30 days after randomization was performed using a 2-level hierarchical mixed-effects logistic model with a random intercept at the patient’s level. Point estimates and 95% confidence intervals were adjusted for age and sex and calculated using ANOVA-like methods for the mixedeffects logistic model. These trials are registred with the European Clinical Trials Database, EudraCT2021-002612-31 (MANTICO2) and EudraCT2021-004188-28 (MONET) and ClinicalTrials.gov, NCT05321394 (MANTICO2) Findings Between March 2022 and February 2023, 991 patients (SOT=332, TGM/CGM =327, NMV/r=332) were enrolled in 15 Italian centersThe overall mean age was 66 years; 482 participants (48.80%) were male and 856 vaccinated with at least a primary course ( 86%). Among the 8/991 hospitalizations observed, one resulted in death. The overall estimate of failure was 0.81% (95%CI; 0.35-1.58%). The odds ratio (OR) for the primary outcome in the NMV/r arm compared to the TGM/CGM and SOT arms was 8.41 (95% CI 1.21 to infinity; p=0.015) and 2.42 (95% CI 0.19 to infinity; p=0.499), respectively. No significant difference was observed between SOT and TGM/CGM (OR 0.32; 95% CI 0.032-1.83; p=0.174). Results were similar when we applied the marginal weighted model accounting for potential residual confounding bias. There was no evidence for a difference in the prevalence of symptoms between treatment groups, except for cough, which was higher in the SOT group compared to the other two groups at the 21-day follow-up (P=0.039) and a higher prevalence of nausea at the 7-day follow-up in the NMV/r group compared to the mAbs group (p=0.036). Interpretation NMV/r was superior to TGM/CGM in reducing hospital admission or death in clinical vulnerable patients with SARS-CoV-2 infection treated within 5 days of symptoms’ onset. No significant difference in symptom prevalence over time across the arms was found. Funding: The trials were funded by the Italian Agency of Drugs (AIFA) in 2021.