Google Trends normalizes search data to make comparisons between terms easier. Search results are normalized to the time and location of a query by the following process: Each data point is divided by the total searches of the geography and time range it represents to compare relative popularity ** The context of our numbers also matters**. We index our data to 100, where 100 is the maximum search interest for the time and location selected. That means that if we look at search interest in the.. How is Google Trends data adjusted? What does a value of 100 mean? Each data point is divided by the total searches of the geography and time range it represents, to compare relative popularity

* What does a value of 100 mean? To prevent unfair weighting, each data point is divided by the number of searches in the region during that time frame*. They are then ranked from 0-100 based on its.. What does a value of 100 mean? - The data is adjusted in proportion to the time/location of the search; this allows for comparisons between terms to be made more easily

Data is adjusted through a search engine, and the value 100 probably is a percent Exploring Trends on your own Continue exploring comparisons of search trends that are interesting to you. You might.. Google Trends display the data of popular searched terms and award them a score from 0 to 100. Google trends data shows relative popularity which means actual search volume for a particular search term of each day within the time range compared with all the searches done on google at that time and location The numbers are scaled on a range of 0 to 100 based on a topic's proportion to all searches on all topics. — trends.google.com So that means that when looking at these values, a value of 100 means that was the peak popularity among those terms (candidates) for that given time frame. A value of 50 would mean that term is half as popular

The **adjusted** R-squared is a modified version of R-squared that accounts for predictors that are not significant in a regression model. In other words, the **adjusted** R-squared shows whether adding additional predictors improve a regression model or not. To understand **adjusted** R-squared, an understanding of R-squared is required The numbers represent the search interest relative to the highest point on the chart for the selected region and time. A value of 100 is the peak popularity of the term, whilst a value of 50 means that the term is half as popular. Scores of 0 mean that a sufficient amount of data was not available for the selected term Google Trends Google app

How is Google Trends data adjusted? What does a value of 100 mean? Using your course project topic as a search term (or several related to your topic), look for: Long-term trends: Is your topic becoming more popular over time? Less? Short-term trends: Does your topic suddenly spike or dip in popularity? Patterns: Does your topic follow some predictable repeated pattern To build a graph the way Google Trends does, you need to take the following steps: Calculate relative popularity as a ratio of the query's search volume to the total number of searches. Scale these values proportionally so that the maximum value is 100. Put the dots on the graph Open Google Trends. Search for a term. In the top right of the chart, click the Embed icon . Copy and paste the HTML code into the body of your webpage. Click Done. Note: The embed feature is not available for all charts The adjusted R^2 value of 65% for this regression implies that the independent variable explains 65% of the variation in the dependent variable. Ideally, a researcher will look for the coefficient of determination, which is closest to 100%. Example #2. Let us try and understand the concept of adjusted R square with the help of another example Google Trends is trends search feature that shows the popularity of a search term in Google. You can view whether a trend is on the rise or declining. You can also find demographic insights, related topics, and related queries to help you better understand the Google trends. How to Use Google Trends: 10 Features for Entrepreneurs 1

- The mean of the dependent variable predicts the dependent variable as well as the regression model. 100% represents a model that explains all the variation in the response variable around its mean. Usually, the larger the R2, the better the regression model fits your observations
- Data Trend Analysis in Google Analytics. Data Analysis. Analysing data trends in Google Analytics is an age-old and powerful tactic that is used to measure the performance of marketing campaigns over time and to predict future outcomes. Following is an example of a data trend in Google Analytics
- al dollars (i.e., not inflation-adjusted)
- Seasonal adjustments provide a clearer view of nonseasonal trends and cyclical data that would otherwise be overshadowed by the seasonal differences. This adjustment allows economists and.
- The volume weighted adjusted price is the true average price of the stock and does not affect its closing price. The VWAP calculation, like the moving average Kaufman's Adaptive Moving Average (KAMA) Kaufman's Adaptive Moving Average (KAMA) was developed by American quantitative financial theorist, Perry J. Kaufman, in 1998

Narrower intervals indicate more precise predictions. Below are the fitted values and prediction intervals for an Input of 10. The model with the high variability data produces a prediction interval that extends from about -500 to 630, over 1100 units! Meanwhile, the low variability model has a prediction interval from -30 to 160, about 200 units A large difference between the two regression R 2 values would indicate a systematic error in the model, since it does not correctly predict the test data with good precision (although it may predict the trend correctly). The larger value of R 2 is not a true test set estimate of model fit, since it comes from a regression model using test set data, while the definition of test set data is that it is not used to fit a model

100% indicates that the model explains all the variability of the response data around its mean. It is important to note that there may be a non-linear association between two continuous variables, but computation of a correlation coefficient does not detect this That does not mean these bonds are necessarily poor investments. Their high yields offset the losses and more, which can be seen by looking at the adjusted closing prices of high-yield bond funds Google Net Worth. As of June 2021, Google net worth is estimated to be around $300 billion. Its parent company Alphabet net worth is estimated to be around $900 billion making it as the third most valuable company behind Amazon and Apple. Google every day makes over $50 million considering they had a revenue of $97.2 billion

100% indicates that the model explains all the variability of the response data around its mean. In general, the higher the R-squared, the better the model fits your data In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced R squared, is the proportion of the variance in the dependent variable that is predictable from the independent variable(s).. It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the testing of hypotheses, on the basis of other related. We used Google Trends to generate data over time on regional interest in dietary In our study, we used an adjusted RSV, where a value of 100 represents the highest popularity of all the phrases being analyzed. GT can recognize a phrase as either a search we calculated the mean ratio to the RSV of lutein for each. Google Trends¶ Google Trends shows how often a search-term is entered relative to the total search-volume. About the data from Google Trends: Numbers represent search interest relative to the highest point on the chart for the given region and time. A value of 100 is the peak popularity for the term. A value of 50 means that the term is half.

Because the daily data from Google Trends are only available in segments of approximately 8 months, we downloaded the daily data in segments and normalized it to the weekly data (which were available for the entire period) to make it comparable across the entire time period Google Trends data have been used previously in research, However, this would mean that if there were seasonal unit roots in . adjusted R² value among the four destinations 2.1 Google Trends Applications 3 STATIONARITY AND DETRENDING 2.1 Google Trends Applications The reason we chose Google Trends data to analyze remodeling cycles is because Google Searches have been used to monitor marketing trends, general interests such as Oscar Awards, u outbreaks (although there are controversies on how e ective it is)

Google Trends data are used to predict the monthly number of foreign arrivals released by the Italian national statistical office, which is the dependent variable. Specifically, we have assessed the contribution of lagged GT variables in a standard ARIMA model and in a time series regression model with seasonal dummies and autoregressive components The data of Google Trends was used to analyze the number of Google searches related to skin problems from January 2004 to December 2019. Thirty-four topics representing dermatologic complaints.

- Google Trends data shows that This is the primary long thesis that has caused these stocks to nearly double in value. Look up the 5 year Google Trend chart. Its flat. Does this mean Etsy.
- The code rnorm(100, mean = 0, sd = 0.2) generates 100 values from a Normal distribution with a mean of 0 and standard deviation of 0.2. This will be our error. This is one of the assumptions of simple linear regression: our data can be modeled with a straight line but will be off by some random amount that we assume comes from a Normal distribution with mean 0 and some standard deviation
- 6 Google Ads Trends You Can't Ignore in 2021 Trend #1: Google Ads Smart Bidding. In recent years, Google has invested heavily in artificial intelligence (AI), and Smart Bidding is one of the many results of that investment. Google's definition is
- The adjusted book value is a measure of a company's valuation after liabilities and assets are adjusted to reflect true fair market value
- Tropical Mean Temperature Trends for the Intervals 1979-2005 and 1958- a a Best estimates and uncertainties given for HadCRUT4 surface trends and maximum trends aloft (between 100 and 500 hPa). Trends using wind shear data have used the respective column temperature data set at reference latitude

- Interpretation. Minitab uses the adjusted mean squares to calculate the p-value for a term. Minitab also uses the adjusted mean squares to calculate the adjusted R 2 statistic. Usually, you interpret the p-values and the adjusted R 2 statistic instead of the adjusted mean squares
- g popular in exa
- Earth Engine's public data catalog includes a variety of standard Earth science raster datasets. You can import these datasets into your script environment with a single click. You can also upload your own raster data or vector data for private use or sharing in your scripts
- us the depreciation of produced capital, depletion of subsoil assets and timber resources, the cost of pollution damages, plus a credit for education expenditures. This dataset includes ANS and its underlying components (including natural resource rents), as well as adjusted Net National Income (aNNI)
- adjusted the time series from the seasonality, which were quartered using the average value of every three months. Then every series was transformed into index numbers based on the maximum value of GT data: each series is 100 in the quarter in which the value of the variable GT is greater, and all other values have been calculated based on these

Assemble the Google Trends Data. The next step is to assemble the data that will be plotted. In the code below, change the usr string to your own Gmail account. Then change psw to your password. These two objects are passed to gconnect() so that your R console can programmatically connect to the Google Trends service. Next create poke utilizing gtrends() with a search pattern, and dates Although chronic obstructive pulmonary disease (COPD) prevalence and mortality rates rise continuously, patients often remain undiagnosed, probably due to a lack of disease-related awareness. The aim of this study was to quantify public interest in COPD by analysing the frequency of web queries via Google. Data from 2004 to 2018 were collected using the search engine query data analysis tool. Children's and women's haemoglobin statuses improved in some regions where concentrations had been low in the 1990s, leading to a modest global increase in mean haemoglobin and a reduction in anaemia prevalence. Further improvements are needed in some regions, particularly south Asia and central and west Africa, to improve the health of women and children and achieve global targets for. Predictions using the last value method. Moving Average. In the moving average method, the predicted value will be the mean of the previous N values. In our context, this means we set the current adjusted closing price as the mean of the adjusted closing price of the previous N days. The hyperparameter N needs to be tuned

- e the relationship between search intensity related to environmental issues and economic growth. Depending on the search term or topic and if said term or topic is measured in no
- If you've done any research on tracking data on your website, you've probably heard about Google Analytics.But what exactly does Google Analytics do? Google Analytics is a free website analytics service offered by Google that gives you insights into how users find and use your website.With Google Analytics, you can track return on investment (ROI) for your online marketing
- ed trends in use of low-value care among individuals enrolled in TM and MA using 4 low-value care composite measures. We conducted the same analysis as described previously and estimated the adjusted mean outcomes for individuals enrolled in TM and MA in each period
- The data comprises over 18 000 bar, which makes the calculation reliable. The data set based on the above currency pairs was used to search for patterns predicting long and short positions. The data set with initial quotes can be found in the attached file named kot60_110101_131231_UA.txt. 2.1. Creating a Target Variabl

- Seasonally adjusted auto sales (independently obtained from the same government source) and personal income line up like this when plotted on the same graph: The strong and generally similar-looking trends suggest that we will get a very high value of R-squared if we regress sales on income, and indeed we do
- Your current half year does not contain any sales because it is the winter season. Do you ask the bank to wait 6 months or do you do something else? This is where Seasonally Adjusted Annual Rate (SAAR) comes to your aid. It is a rate adjustment used for economic or business data that attempts to remove the data's seasonal variations
- The CPI inflation calculator uses the Consumer Price Index for All Urban Consumers (CPI-U) U.S. city average series for all items, not seasonally adjusted. This data represents changes in the prices of all goods and services purchased for consumption by urban households.
- Pneumonia has a high human toll and a substantial economic burden in developed countries like Japan, where the crude mortality rate was 77.7 per 100,000 people in 2017. As this trend is going to continue with increasing number of the elderly multi-morbid population in Japan; monitoring performance over time is a social need to alleviate the disease burden

Object Measuring handgrip strength is a useful method to evaluate sarcopenia. No study has shown the trends of handgrip strength to weight ratio among Korean adolescents by year. This study aimed to determine the trends of handgrip strength among Korean adolescents using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Data of 2304 adolescents who participated in. HOME VALUES. Zillow Home Value Index (ZHVI): A smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type.It reflects the typical value for homes in the 35th to 65th percentile range. The raw version of that mid-tier ZHVI time series is also available Trends of Unadjusted Cost Differences for Hypertension. The unadjusted mean annual medical expenditure (all inflated to 2016 US dollars) attributable to patients with hypertension was $9089 (95% CI, $8900-$9278) in the pooled 12‐year data

- 1. Introduction [2] As assessed from the modern satellite passive microwave data record that began in October 1978, Arctic sea ice extent exhibits downward linear trends in all months. The trend is largest for September (the end of the summer melt season), and appears to have steepened with time [Stroeve et al., 2012].Through 2011, the linear rate of decline for September is −12.9 ± 1.47%.
- ation Survey (NHANES) reported declining blood cholesterol.
- MSL trends for sites with more than 15 complete years of Revised Local Reference (RLR) information in the Permanent Service for Mean Sea Level (PSMSL) data set for the years 1901 onwards (Only data from complete years, i.e. which contain data from all 12 months of the year, have been used in the computations)

Inflation-Adjusted Data. Incorporating inflation data to historical total returns and relative prices produces the following inflation-adjusted graph: As can be seen, the stock market was very profitable, in real terms, in the 1950 to 1965 and 1983 to 2000 periods We analyse and compare NBA and Euroleague basketball through box-score statistics in the period from 2000 to 2017. Overall, the quantitative differences between the NBA and Euroleague have decreased and are still decreasing. Differences are even smaller after we adjust for game length and when playoff NBA basketball is considered instead of regular season basketball (a) Adjusted global-mean annual-mean temperature for the period 1856-2010, after ENSO, volcano aerosol, and solar influences have been removed by regression. The order of the noise is found to be p = 4. The 20-yr moving average is shown in blue, and the linear trend is fitted to the period 1979-2010 in red Trend of Mean Age at Onset Compared to the Mean Age of the corresponding to a crude annual incidence rate of 3.03 per 100 000 population (95% CI, 2.85-3.23) and an adjusted incidence rate of 2.78 per 100 000 population (95% in particular in Western countries, there are few data on the long-term epidemiologic trends of.

- ed the mean intake of beef, pork, lamb or goat, chicken, turkey, fish, dairy, eggs, legumes, and nuts and seeds (grams per kilogram of body weight) among adults and according to subgroups, including chronic disease status
- Besides, given its simple structure, good flexibility and excellent potential to evaluate the data of the α-Sutte Indicator, it seems that this method may be transferable to make time-series forecasting for the trends of the epidemiological indicators (such as prevalence, morbidity and mortality) in other countries, territories or areas during the pandemic period or other types of data (such.
- Introduction In this piece we will cover Adjusted Plus-Minus (APM) / Regularized Adjusted Plus-Minus (RAPM) as a method for evaluating skaters in the NHL. Some of you may be familiar with this process - both of these methods were developed for evaluating players in the NBA and have since been modified to do the sam
- Increased temperature trends at high latitudes are a result of the inclusion of the missing humidity temperatures (i.e., the unadjusted data include only temperature data where humidity observations also exist, while the adjusted data include all temperature data and interpolated humidity) and the adjustment to Russian temperatures (Figs. 8a and 9c)

So while historical data can surely be informative, succeeding in this industry means being able to read the tea leaves and detect changing trends that may make tomorrow different from yesterday. What Does This Mean? Headlines in the tech media often speak of the growing number of tech unicorns (companies valued at over $1 billion) Temperature trends over the 16 year period January 1997-December 2012 in °C decade −1 for HadCRUT4 and three near-global reconstructions: GISTEMP extrapolated surface temperatures, UAH satellite data and NCEP/NCAR reanalysis data. Areas with no coverage are shown with hatching. Note that the cylindrical projection exaggerates the missing area at high latitudes

- trendsceek identifies genes with significant spatial trends in single-cell spatial expression data, as well as in low-dimensional projections of dissociated single-cell RNA-seq data. As methods.
- These data systems rely on accurate birthweight measurement, but despite increasing prevalence of facility births, many newborns are not weighed, and when weighed, so-called heaping at specific birthweights (eg, multiples of 100 g or 500 g) is common
- Prospective registries have proven potential to assess the safety, quality, and value of spine care at both individual patient level and at the population level. 36, 63-65 The registries provide reliable and expeditious access to outcomes data such as complications, readmission, pain, disability, quality of life, patient satisfaction, and cost-effectiveness. 63 Moving forward, individual.
- Where does data on OpenAQ come from. Openaq.medium.com DA: 17 PA: 46 MOZ Rank: 82. Please note: Find the OpenAQ Data Policy here.; More FAQs on data and the OpenAQ Platform and Community can be found here.; So we've got a lot of data, but, in point of fact, we do not measure any of it ourselves — we aggregate it from public real-time data sources provided by official, usually government.
- Mean imputation is the practice of replacing null values in a data set with the mean of the data. Mean imputation is generally bad practice because it doesn't take into account feature correlation. For example, imagine we have a table showing age and fitness score and imagine that an eighty-year-old has a missing fitness score
- We conducted a retrospective analysis of publicly available data from Google Trends (GT; Google, Mountain View, CA, USA) to explore online sepsis information-seeking behaviors worldwide between 24 June 2012 and 24 June 2017 [].An exemption from review was granted by the Emory University Institutional Review Board
- Mortality Trends in the United States, 1900-2018. These graphics of U.S. mortality trends since 1900 highlight the differences in age-adjusted death rates and life expectancy at birth by race and sex; childhood death rates by age group; and age-adjusted death rates for five selected major causes of death. Select a dashboard from the left side.

It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess. Inflation Adjusted Real Estate Prices- Lets take a look at the idea that housing prices always go up. Of course, each neighborhood is different, so some neighborhoods might be going down while a few miles away housing prices are skyrocketing but by looking at the nationwide average and by adjusting those prices for inflation we can get a better picture of how real estate prices really ac With a solid understanding of these 100 hotel trends, we're prepared to play a successful part in the future of travel. There's no doubt that technology, sustainability, and security will play a greater role in hotel operations in the next decade. Get a head start and begin to implement some of these trends at your hotel today In Summary: 2021 Will Be The Year of People First. Omnichannel marketing is a great place to close this article on 2021 digital marketing trends because omnichannel marketing captures what we think will be the guiding high-level trend in 2021 and beyond: putting people at the center of everything you do

WHO's Global Health Estimates provide latest available data on causes of death globally, by region, by sex and by income group. They are published every 3 or 4 years and identify trends in mortality over time, which can and are used for decision-making on global health policy and resource allocation Background The true causes of the obesity epidemic are not well understood and there are few longitudinal population-based data published examining this issue. The objective of this analysis was to examine trends in occupational physical activity during the past 5 decades and explore how these trends relate to concurrent changes in body weight in the U.S. Methodology/Principal Findings.

Objective To compare trends in readmission rates among safety net and non-safety net hospitals under the US Hospital Readmission Reduction Program (HRRP). Design A retrospective time series analysis using Medicare administrative claims data from January 2008 to June 2015. Setting We examined 3254 US hospitals eligible for penalties under the HRRP, categorised as safety net or non-safety net. Figure 1A shows the time trends for age-adjusted mean steps per day among the Japanese population from 1995 to 2016. According to our visual inspection based on the descriptive data, it seemed that both men and women were most active between 1997 and 2000 in terms of pedometer-determined PA For assessing human leukocyte antigen compatibility in deceased donor kidney transplantation, virtual crossmatch is used as an alternative to physical crossmatch and has potential to reduce cold ischemia time. The 2014 United States kidney allocation system prioritized highly sensitized candidates but led to increased shipping of kidneys Trends in mean total costs are shown by stage at diagnosis. Costs were estimated from Medicare reimbursement for all health services, adjusted for inflation and geographic variability. There appeared to be a marginal increase in mean total costs for the overall cohort between 2000 and 2007 (P = .05)

Using all available opportunistic data from the same periods, mean standard errors of trends were 0·001 and 0·002 for butterflies and dragonflies, respectively (based on 37 and 40 species with mean number of 1 × 1 km squares 6206 and 4245), thus considerably lower Background: Under the inpatient prospective payment system (IPPS), Medicare assigns hospital discharges to medical severity-adjusted diagnosis related groups (MS-DRGs), and determines a fixed payment amount for each discharge based on its MS-DRG that is adjusted annually based on providers' reported costs.Trends in these capitated reimbursement rates may affect the incentive for. Recent data releases show rather poor income growth. Common sense would tell you these numbers are averages - and this would mean: more-and-more new hires are being paid near minimum wage; and/or Background There is widespread concern over the recruitment and retention of GPs in England. Income is a fundamental consideration affecting the attractiveness of working in general practice. Aim To report on trends in average incomes earned by GPs in England, adjusted for inflation and contracted time commitment. Design and setting Postal surveys of random samples of GPs working in England in.

- Trends and disparities among those with COPD were similar, although the proportion going without needed medications worsened, rising by an adjusted 7.8 percentage points. Interpretation Coverage losses among persons with airways disease in the first decade of the twenty-first century were reversed by the ACA, but neither care affordability nor disparities improved
- Data as of 15:00ET on 10-Jun-2021, or as noted below. Johns Hopkins dashboard over 174.52M worldwide cases (+390K vs prior) and 3.76M deaths (+13,976) -- case growth +0.2% d/d over 33.41M cases in the US (+18K) and 598K deaths -- case growth +0.1% d/d ~10.1% of US population infected; 1 in 551 Americans killed (~330M) Total tested in US.
- METHODS: We summarized data from the 2016 iteration of the Global Burden of Disease Study to provide current (2016) and historical estimates for all-cause and cause-specific diseases and injuries using mortality, years of life lost, years lived with disability and disability-adjusted life years in Canada. We also compared changes in life expectancy and health-adjusted life expectancy between.
- Thus, income data in this section refer to the 1970-2018 period and the counts of people from the same survey refer to the 1971-2019 period. ↩; The S&P/Case-Shiller U.S. National Home Price Index increased from 80 in January 1995 to 185 in June 2006 (January 2000=100)

This framework comprised expressions for probabilities, mean, variance, and return-values. We differentiated these statistics with respect to time and compared them to trends in number of rainy days and the mean rainfall intensity based on 1875 rain gauge records with more than 50 years of valid data over the period 1961-2018 In this study, we used a comprehensive set of statistical metrics to investigate the historical trends in averages and extremes of rainfall and temperature in Sri Lanka. The data consist of 55 years (1961-2015) of daily rainfall, maximum temperature ( T max ), and minimum temperature ( T min ) records from 20 stations scattered throughout Sri Lanka

The aims of the current study were to analyze the evolution of players' age in the UEFA Champions League since the start of its modern-day format in 1992-1993 up until 2017-2018 and to determine how the players' age relates to their market value. The sample consisted of all players participating in the UEFA Champions League from the 1992-1993 to 2017-2018 seasons (n = 16062) Time series datasets can contain a seasonal component. This is a cycle that repeats over time, such as monthly or yearly. This repeating cycle may obscure the signal that we wish to model when forecasting, and in turn may provide a strong signal to our predictive models. In this tutorial, you will discover how to identify and correct for seasonality in tim This adjusted data does not replace the old site record—instead, it is appended to the observed record for the new site. In this way, (the difference between the individual daily or monthly value and the long-term mean, Statistical detection must also take into account the trends in data—otherwise results will be unreliable For data to be stationary, the statistical properties of a system do not change over time. This does not mean that the values for each data point have to be the same, but the overall behavior of the data should remain constant. From a purely visual assessment, time plots that do not show trends or seasonality can be considered stationary Secular trends in regional differences in nutritional biomarkers and self-reported dietary intakes among American adults: National Health and Nutrition Examination Survey (NHANES) 1988-1994 to 2009-2010 - Volume 21 Issue

In recent years, state-space models have been employed as powerful tools in the analysis of population abundance and trends (Berliner 1996, Royle and Dorazio 2008).These models have a number of distinct advantages over traditional analyses of survey data (Cressie et al. 2009).By explicitly separating the state process (the fixed and random effects that cause variation in population abundance. This study quantifies the present-day global and regional distributions (2010-2014) and trends (2000-2014) for five ozone metrics relevant for short-term and long-term human exposure. These metrics, calculated by the Tropospheric Ozone Assessment Report, are: 4th highest daily maximum 8-hour ozone (4MDA8); number of days with MDA8 > 70 ppb (NDGT70),.. Providing equal access to health care is an important objective in most health care systems. It is especially pertinent in systems like the Swedish primary care market, where private providers are free to establish themselves in any part of the country. To improve equity in access to care, 15 out 21 county councils in Sweden have implemented risk-adjusted capitation based on the Care Need.