Sentences with phrase «large sample sizes»

In fact, it is possible that child emotional or behavioral problems lead to paternal and / or maternal mental health problems, although the literature on maternal depression and other aspects of maternal mental health clearly indicate that in most such cases it is maternal mental health that influences child mental health.1, — , 12 Large sample sizes such as the 1 in this study sometimes result in statistically significant findings that may not be clinically significant, although this does not seem to be the case in this study, as paternal mental health problems or depressive symptoms were associated with considerably increased risks of child emotional or behavioral problems.

Subgroup analyses examining associations between recruitment source and intervention effectiveness require large sample sizes.17 We have recently published one of the largest randomised trials of an internet intervention, the EVIDENT trial.3 Over 1000 participants were randomised for this trial that demonstrated the effectiveness of the intervention (Deprexis) for mild to moderate depressive symptoms.

Some severe disorders have low base rates, between 1 % and 4 %.29, 30 Low base rates require large sample sizes to generate reliable estimates.31 Some studies sampled too few subjects to generate reliable rates even for the more common disorders.18, 21

While this method is useful to gain context specific insights into the effectiveness of climate policies, statistical studies based on large sample sizes allow analysts to control for various factors and yield generalizable results.

This «study of studies» has the advantage of large sample sizes that are likely to be statistically significant.

First, quality studies in education (large sample sizes, randomized, cross-over design, longitudinal, etc.) are very expensive and rare.

In this session we show that a range of approaches, including fine - mapping with very large sample sizes (which separate SNPs in high LD), or samples from multiple ethnicities (which have different LD patterns) can often identify one, or only a few, likely causal variants.

Having large sample sizes from many species was key.

Standardized husbandry in the dairy industry, combined with systematic milking procedures, detailed record - keeping, and large sample sizes made the dairy cow a powerful model for the exploration of milk synthesis.

Researchers compensate for the lack of control by using large sample sizes — some vitamin D studies track 50,000 people — and applying statistical techniques.

With the graveyard's large sample sizes, they hope to compare the men and women of Badia Pozzeveri to see who was better fed.

The study, with its exceptionally large sample sizes, is «a major advance,» says David Goldman, chief of the lab of neurogenetics at the National Institute on Alcohol Abuse and Alcoholism in Bethesda, Maryland.

When Nweeia learned about narwhal molting for the first time, he knew that he had to part with the traditional scientific approach that validates facts through large sample sizes.

However, because only a few studies were graded to be of high quality, we suggest that further research, conducted with good methodology and large sample sizes, should be carried out to strengthen the validity of these observations.

Also, it is difficult to show statistical significant differences in mortality even with very different numbers because the mortality rates are so low, you need very large sample sizes that aren't often found.

Such success over large sample sizes indicates that the market is slightly inefficient when accounting for discrepancies in motivation and also tends to overreact to recent poor performances.

Large sample sizes allow you to more accurately observe advantages that you may hold over the sportsbooks.

Consistent results, large sample sizes and the ability to explain your edge.

Large sample sizes allow you to more accurately observe advantages that you may hold over the sportsbooks, yet it never ceases to amaze how much stock bettors will place in the performance of a team over the past five games.

Psychiatric diseases, since they are the result of a complex mix of genetics, environment, and behavioral factors, require large numbers of people, or what's known as a large sample size.

To get a larger sample size, the research team looked at the companies started between 2006 and 2016.

But before everything actually accelerates, the medical research industry will need three things: (1) A larger sample size; (2) A way of letting people share their information in a granular fashion and; (3) A place to put the terabytes of medical data that ResearchKit generates.

Augmenting your data sourcing efforts with GCS also offers the ability to gather a larger sample size of data without increasing your workload significantly — and we all know that more data from different sources leads to more informed and statistically significant insights.

Remember, it's your results over a large sample size of trades that matters.

... Or the Tezos raise, which was 30 times the size of the Ethereum raise with what we should expect are many, many more contributors, thus offering an ostensibly much larger sample size:

A major problem with this theory is that the sample size of trading days is small (5), compared with the January barometer (typically about 20 — which is also not a large sample size), to be a reliable predictor of the rest of the year.

It just means that there is too much randomness in the small sample size and that the system should be tested over more games (a longer time period or larger sample size).

The larger the sample size, the more reliable the system matches.

We have spoken in the past about the key characteristics for a winning betting system, and one of the most important is a large sample size.

This system has a strong driving hypothesis, consistent year - to - year results and a very large sample size.

Therefore, the significantly larger sample size allows us to get a much more accurate look at the sports betting marketplace.

Both systems have a large sample size, consistent year - to - year results, and a solid driving hypothesis which are the three main criteria for a winning betting system.

While we have already created a winning betting system with a large sample size and strong driving hypothesis, there was one more historically profitable betting trend to layer onto our system.

This includes having a large sample size, being open - minded and developing new theories as opposed to buying into widely held public beliefs.

In my opinion we could raise a further 50 - 55m if we sell the players that have been given enough chances to have a large sample size concluding that they are simply not good enough.

I believe, a good exercise would be to take a sufficiently large sample size of players who played for Arsenal and some other club for a long period, say at least 3 - 4 years and compare their injury records in the two phases (number, frequency and nature of injuries incurred).

It's also important to note that this system fits the three common characteristics of a winning betting system: large sample size, consistent year - to - year results and clearly defined data ranges to avoid custom - fitting the data.

With a large sample size, consistent year - to - year results, and a strong guiding philosophy this system clearly fits the three main characteristics of winning betting systems.

As you can see from the screenshot below, this simple step nearly doubled our return on investment while maintaining a large sample size:

Moreover general statistics would dictate the larger the sample size the greater propensity there is for a statistic to taper off.

Call me crazy but I just think that I would give a larger sample size of how supposedly great he is.

Although the highest ROI correlates with visitors receiving less than 30 % of spread bets, we will focus on teams receiving less than 35 % of spread bets due to the significantly larger sample size and units won.

This system has the large sample size, strong driving hypothesis and consistent year - to - year results that we look for in a winning betting system.

When building a data - driven betting system, I usually look for a large sample size, consistent year - to - year results, and a strong guiding philosophy.

While these results were encouraging, we knew that with such a large sample size on a basic system it would be easy to improve our expected return on investment.

It also features the type of strong driving hypothesis, large sample size, and consistent year - to - year results that we look for in our data - driven betting systems.

Knowing that we had already developed a profitable system with a large sample size and consistent year - to - year results, we wanted to continue layering filters to improve our return on investment (ROI).

This has the unfortunate side effect of implying that you can't evaluate a player with reasonable certainty until he has played for years and you have a large sample size.

Betting against the public has been supported by years of research and with over 500 past matches we clearly have a large sample size, but what about the year - to - year results?

That said, we prefer the larger sample size that was used in the article.