scholarly journals SB1 COMPARISON OF DIFFERENCE-IN-DIFFERENCE, PROPENSITY SCORE MATCHING AND INSTRUMENTAL VARIABLES IN ESTIMATING COST DIFFERENCES BETWEEN TWO COHORTS

2011 ◽  
Vol 14 (3) ◽  
pp. A4
Author(s):  
Z. Cao ◽  
X. Song
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Instrumental Variables ◽  
Difference In Difference ◽  
Cost Differences

scholarly journals Postoperative non-steroidal anti-inflammatory drug use and oncological outcomes of rectal cancer

BJS Open ◽  
2021 ◽  
Vol 5 (1) ◽  
Author(s):  
O Grahn ◽  
M Lundin ◽  
M-L Lydrup ◽  
E Angenete ◽  
M Rutegård
Keyword(s):  
Rectal Cancer ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Instrumental Variables ◽  
Cox Regression ◽  
Recurrence Free Survival ◽  
Free Survival ◽  
Oncological Outcomes ◽  
Anti Inflammatory ◽  
Instrumental Variables Approach

Abstract Background Non-steroidal anti-inflammatory drugs (NSAIDs) are known to suppress the inflammatory response after surgery and are often used for pain control. This study aimed to investigate NSAID use after radical surgical resection for rectal cancer and long-term oncological outcomes. Methods A cohort of patients who underwent anterior resection for rectal cancer between 2007 and 2013 in 15 hospitals in Sweden was investigated retrospectively. Data were obtained from the Swedish Colorectal Cancer Registry and medical records; follow-up was undertaken until July 2019. Patients who received NSAID treatment for at least 2 days after surgery were compared with controls who did not, and the primary outcome was recurrence-free survival. Cox regression modelling with confounder adjustment, propensity score matching, and an instrumental variables approach were used; missing data were handled by multiple imputation. Results The cohort included 1341 patients, 362 (27.0 per cent) of whom received NSAIDs after operation. In analyses using conventional regression and propensity score matching, there was no significant association between postoperative NSAID use and recurrence-free survival (adjusted hazard ratio (HR) 1.02, 0.79 to 1.33). The instrumental variables approach, including individual hospital as the instrumental variable and clinicopathological variables as co-variables, suggested a potential improvement in the NSAID group (HR 0.61, 0.38 to 0.99). Conclusion Conventional modelling did not demonstrate an association between postoperative NSAID use and recurrence-free survival in patients with rectal cancer, although an instrumental variables approach suggested a potential benefit.

The SOE Channel of Monetary Policy Transmission: Evidence from China's Economic Stimulus Package

2021 ◽  
pp. 1-21
Author(s):  
Wenbin Chen ◽  
Shi-Zhuan Han ◽  
Jie Li ◽  
Tianhang Zhou
Keyword(s):  
Monetary Policy ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Bank Loans ◽  
Monetary Policy Transmission ◽  
Difference In Difference ◽  
Policy Transmission ◽  
High Level ◽  
Stimulus Package

Abstract We examine the state-owned enterprises (SOEs) channel in monetary policy transmission in the context of China's 2008 stimulus package. Using a difference-in-difference approach, we show that the higher SOE share in the cities after the stimulus package, the more bank loans issued in the cities. Furthermore, we find that the role of SOEs in monetary policy transmission is more significant in underdeveloped cities and cities with a high level of government intervention. We adopt propensity score matching difference-in-difference to deal with potential endogeneity problem. The baseline results also survive a series of robustness tests.

The Importance of Clinical Variables for Propensity Score Matching When Comparing Costs: The Case of ESA Treatments for Chemotherapy Induced Anemia

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4695-4695
Author(s):  
Daniel Polsky ◽  
Daria Eremina ◽  
Gregory P. Hess ◽  
Jerrold Hill ◽  
Scott Hulnick ◽  
...  
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Linear Models ◽  
Mean Difference ◽  
Cost Models ◽  
Original Sample ◽  
Treatment Groups ◽  
Clinical Variables ◽  
Patients With Cancer ◽  
Cost Differences

Abstract Background: The erythropoiesis-stimulating agents (ESAs) epoetin alfa (EA) and darbepoetin alfa (DA) are treatments for chemotherapy-induced anemia. Therapy choice depends on many factors, including cost. Previous analyses have demonstrated differences in the characteristics of patients receiving EA vs. DA. We estimated cost differences between DA and EA in patients with cancer receiving chemotherapy using a propensity score matched analysis of baseline patient characteristics with and without hemoglobin (Hb) values. Methods: Data were extracted from electronic medical records in two US databases between January 2004 and December 2006. The study sample included 6743 patients receiving chemotherapy, with ≥ 1 visit during the study period, who received an ESA during a chemotherapy episode. Episodes of chemotherapy care were constructed using a 90 day gap in administration to identify the start and end. Patients receiving both, or neither, DA and EA during their initial chemotherapy episode, or with missing descriptive data were excluded. Drug costs were calculated from cumulative dose multiplied by 106% of the average sales price (ASP) for DA or EA. Two propensity score matches were conducted: first using variables available in administrative billing claims systems, then adding the baseline Hb test result. Regression-adjusted cost differences were estimated with and without baseline Hb, using generalized linear models. Results: Using baseline Hb as a variable resulted in a better match of the baseline characteristics for the EA and DA treatment groups compared to the original sample or the matched sample without baseline Hb. Mean ESA costs for the original sample were $4171 for EA and $3811 for DA (mean difference: $360; P <0.001, SE $99). With propensity score matching without baseline Hb, mean estimated costs were $3836 for EA and $3599 for DA (mean difference: $237; P = 0.053, SE $123). With propensity score match including baseline Hb, mean costs were $3965 for EA and $3536 for DA (mean difference: $429; P = 0.001, SE $125). Conclusions: Addition of baseline Hb as a variable in propensity score and ESA cost models affects ESA treatment cost estimates in patients with cancer receiving chemotherapy. Cost comparisons based on observational data should use analytical methods that account for differences in clinical variables between treatment groups.

Propensity-Score Matching with Instrumental Variables

2001 ◽  
Vol 91 (2) ◽  
pp. 119-124 ◽  
Author(s):  
Hidehiko Ichimura ◽  
Christopher Taber
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Instrumental Variables

Impacts of Internet Use on Senior Citizens’ Depressive Symptoms in China: Urban-Rural Differences (Preprint)

2020 ◽  
Author(s):  
Kai Sun ◽  
Yuxiang Chris Zhao ◽  
Xiaofeng Tao ◽  
Junjie Zhou ◽  
Qianqian Liu
Keyword(s):  
Regression Analysis ◽  
Depressive Symptoms ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Internet Use ◽  
Senior Citizens ◽  
The Internet ◽  
Depression Symptoms ◽  
Difference In Difference ◽  
Urban Rural

BACKGROUND Although existing studies report that Internet use can help senior citizens coping with depressive symptoms, so far limited studies have explored the impacts of Internet use on urban and rural senior citizens’ depression symptoms. OBJECTIVE This study aims to address the above gap and explore the impacts of Internet use on urban and rural senior citizens’ depressive symptoms in China. METHODS We use the data from the China Health and Retirement Longitudinal Study (CHARLS). We use the panel-data regression to examine the relationship between Internet use and depression. In order to obtain robust evidence, we built a treatment group by selecting senior citizens who did not use the Internet in 2013 (Wave 2) but did use it in 2015 (Wave 4), and a control group by selecting senior citizens who did not use the Internet in either Wave based on the propensity score matching (PSM) approach. We then examined the impacts of Internet use with linear regression analysis based on the difference-in-difference (DID) approach. RESULTS The empirical results indicate that Internet use could significantly alleviate rural senior citizens’ depression (β=-2.187, P=.006). The Frequency of Online have consistent effect on depression (β= -1.091, P=.001). In addition, the impacts of Internet use on rural senior citizens’ three specific depressive symptoms are significant (“I had trouble keeping my mind on what I was doing”, β= -0.537, P=.008; “I felt depressed”, β= -0.315, P=.014; “I felt everything I did was an effort”, β= -0.355, P=.021). The propensity score matching and difference-in-difference analysis is consistent with the results of panel date regression analysis. CONCLUSIONS Urban-rural differences exist in the impacts of Internet use on senior citizens’ depressive symptoms. Rural senior citizens’ depressive symptoms can be alleviated by Internet use and the frequency of Internet use. Policy makers should provide rural senior citizens more opportunities to access the Internet and more Internet-skill trainings to enable them to better utilize the Internet.

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