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# Statistic reporting

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## General notes:

When reporting multiple statistics within parentheses, separate each statistic with a semicolon. For example: (P=.50; OR 2.72, 95% CI 0.45-2.6). Do not use possessives for the name of any statistical test (see Use of possessives with eponyms).

Omission of Leading Zero We follow the guidelines set out by AMA (Section 19.7.1)

AMA states that a zero should be placed before the decimal point for numbers less than 1, except when expressing the 3 values related to probability: P, α, and β. These values cannot equal 1, except when rounding. Because they appear frequently, eliminating the zero can save substantial space in tables and text. (Although other statistical values also may never equal 1, their use is less frequent; to simplify usage, the zero before the decimal point is included.)



1 − β=.80

Our predetermined α level was .05.

BUT: κ=0.87

Percentages and Decimal Places If N < 100, there is no decimal point in the percentage. If N is 100 to 999, 1 decimal point is reported. If N ≥ 1000, 2 decimal points are reported. BUT: If a table contains mixed denominators, be consistent and use, for example, 1 decimal point consistently even if some denominators are less than 100. See AMA 2.13.9, 17.3.1, and 17.3.2. N=87, 45%

N=356, 45.1%

N=1024, 45.13%

Note: Do not use n=488/550, 88.7%; instead, it should be only 488/550 (88.7%).

Percentages Within a Sentence Preferred JMIR style is to always make clear what the numerators and the denominators are. Of note, do not add a 0 after the decimal if the percentage value is a whole number, (ie, 64/100=64%, not 64.0%).

In expressing a series of proportions or percentages drawn from the same sample, the denominator need be provided only once.

Of the 200 patients, 6 (3%) died, 18 (9%) experienced an adverse event, and 22 (11%) were lost to follow-up.

Example I:

“the majority of participants (59%) felt that…”

should be revised to

“the majority of participants (59/100, 59%) felt that….” NOT “the majority of participants (59%, 59/100) felt that….“

or if the percentage is used in the sentence,

“…, where 59% (59/100) of the participants felt that…”.

Example II:

“a vast majority (n=488, 88.7%) of participants”

should be changed as follows:

“a vast majority (488/550, 88.7%)” (Note: The “n” has been dropped and the “N” value (ie, 550) has been added). When reporting multiple statistics within parentheses, separate each statistic with a semicolon.

Example III:

“a vast majority (488/550, 88.7%; P=.002)”

Do not use square brackets within parentheses for statistics. Separate values with a comma if statistics are linked (ie, % and numerator/denominator); separate values with a semicolon if statistics are unlinked (ie, % and odds ratio).


“The most common functions among studies that involved children with special needs were consultation (8 studies [73%]) and diagnosis (7 studies [64%]). ”

Chi-square test Include the degrees of freedom (subscript). Authors tend to not include degrees of freedom; query the author if it is not provided. Degrees of freedom are subscripted; chi-square symbol is italicized. Chi-square value should be reported to only 1 decimal place. When reporting chi-square values in a table, include the degrees of freedom in parentheses, eg, chi-square (df). The abbreviation for degrees of freedom (df) does not need to be expanded; it should be italicized (AMA glossary of statistical terms 20.1). Example:

In text: Screen_Shot_2020-06-05_at_4.20.42_PM.png

In table: Chi-square (df)

Mean, standard deviation, standard error, and range Equal signs are not used; separate the value from the statistic with a space. Examples

mean 4.71 (SD 0.47)

range 4-5

SE 2.55

When reporting multiple statistics in a sentence, use a semicolon to separate the terms.

Example: “The mean age of the participants (mean 4.71, SD 0.47; range 4-5)…”

For mean (SD), we prefer not to use the +/- sign. Instead, an expression like 1.11 ± 2.33 should be formatted as “1.11 (SD 2.33).” It is also wise to add a query notifying the author(s) of this change, in case there are also other statistics that have also been formatted by authors with a +/- sign (eg, SE) and they now need to specify the expression.

When reporting a value that is calculated from a mean and SD value, report it in the following manner: Mean+SD=1.6

Note: When reporting mean and SD in a table, include the mean and SD in the same column with the heading “mean (SD)”.

As of December 4, 2013, AMA no longer requires the expansion of “SD” or “SE” in the text (Section 20.9, page 894 in the print) — See Which abbreviations don't need to be expanded?

Odds ratio and confidence interval ORs should always be presented with CIs Include 0 before the decimal point If one value in the CI range is negative, then “to” should be used rather than a hyphen OR 1.2 (95% CI 0.9-2.4)

OR 1.2% (95% CI 0.8%-1.6%)

95% CI –0.1 to 0.8

Note: For consistency, use the “x to y” format for all CIs when some include a negative number; ie, use the “to” construction for positive ranges as well if it needs to be used for a negative. This is most important in tables. Avoid brackets within parentheses. If brackets within parentheses are necessary, use square brackets. We never use parentheses within parentheses. In addition, avoid using parentheses inside another set of parentheses altogether, eg, (OR 2.92 (2.36 - 3.62)) should be rewritten as (OR 2.92, 95% CI 2.36-3.62). CI does not need to be expanded (Section 14.11, page 504 in the print; see Which abbreviations don't need to be expanded? ). When defining “OR” within parentheses, use square brackets. Example: (odds ratio [OR] 2.92, 95% CI 2.36-3.62). Note that OR needs to be defined in tables (through a footnote or in the caption). Confidence limit Upper and lower boundaries of the confidence interval, expressed with a comma separating the 2 values.

Example: The mean (95% confidence limits) was 30% (28%, 32%).

Interquartile range Include 0 before the decimal point. Should be formatted as: IQR 5 (ie, no equal sign).

P value From our instructions for authors:


(Again, this is the primary responsibility of the academic editor, but the copyeditor acts as a second line of defense if this has been overlooked by the editor/section editor) Note for copyeditor: point author to the relevant section in the Instructions for Authors, if P values are missing (ie, “no significant differences were found…” without stating the P-level), incorrectly reported, or replaced by statements of inequality (or in Tables * / ** footnotes) such as P<.05. The actual P value should be expressed rather than a statement of inequality (P=…), unless P<.001 or P>.99 or P=0 (which should be changed to P<.001) or P=1 (which should be changed to P>.99). In other words, for expressions like P<.05, authors should be queried to provide the actual P value. P values cannot be 0 or 1—change to <.001 or >.99, respectively. Note for copyeditor: add a comment to the manuscript in copyediting saying something like “Because P values theoretically cannot reach 1, AMA Manual of Style guidelines are that the highest P value to report is ‘P>.99’ so I have changed them accordingly” (and similar for P=0). P values less than .001 (including 0.000) are not allowed and are to be converted to the expression P<.001. In other words, for example, P<.0001 or P=.0005 must be rewritten as P<.001. P is italicized and capitalized (Note: Our typesetting scripts are actually intelligent enough to convert the P to italics if the copyeditor forgets this). DO NOT use zero before the decimal point. The actual value of P should be expressed to two digits, whether or not it is significant. If P<.01, P should be expressed to three digits. When rounding, 3 digits are acceptable if rounding would change the significance of a value (eg, P=.049 rounded to .05). No spaces in expressions with mathematical operators. Remove these spaces to adhere to our preferred format without blanks. The same is true for other equality and inequality expressions (eg, P < .001 should be changed to P<.001 and n = 12 should be corrected to n=12). In a table, the column heading should be “P value” not “P”. Note that “value” should not be italicized. Examples:







NOTE for P values for very large sample sizes (according to AMA guidelines)

Excerpt from AMA: “Though our style manual recommends (Section 20.9, page 888 in the print) that ”[expressing] P to more than 3 significant digits does not add useful information to P<.001,“ in certain types of studies (particularly GWAS [genome-wide association studies] and other studies in which there are adjustments for multiple comparisons, such as Bonferroni correction, and the definition of level of significance is substantially less than P<.05) it may be important to express P values to more significant digits. For example, if the threshold of significance is P<.0004, then by definition the P value must be expressed to at least 4 digits to indicate whether a result is statistically significant. GWAS express P values to very small numbers, using scientific notation. If a manuscript you are editing defines statistical significance as a P value substantially less than .05, possibly even using scientific notation to express P values to very small numbers, it is best to retain the values as the author presents them.”

If a study has a very large sample size, it may be necessary to report P values to a value smaller than P<.001 in order to show statistical significance. This will be up to editorial discretion.

N and n N designates the entire population under study. n designates a sample of the population under study. Do not insert spaces before and after the sign, and delete spaces on either sides of mathematical operators, except in equations. Examples:



F test Degrees of freedom are subscripted in the text. In a table, degrees of freedom are included in parentheses after the number; ie, “F test (df)” Example:


t test t is italicized. Include the degrees of freedom (subscript). Include 0 before the decimal point. Authors must include whether the test is 1-tailed or 2-tailed Authors tend to not include degrees of freedom; query the author if it is not provided. Example:


Effect size Include 0 before the decimal point. …an effect size of 0.277 standard deviation units.

Cronbach alpha DO NOT use “Cronbach’s” alpha. There is no zero before the decimal point. Example:

Cronbach α=.78

Cohen d DO NOT use “Cohen’s” d with the possessive Include a zero before the decimal point if the value is less than 1. Example:

Cohen d=0.29

Cohen d=1.45

Beta level There is no zero before the decimal point. Example:


Spearman rank correlation The symbol is ρ (rho). Include a zero before the decimal point if the value is less than 1. Example:


Kappa statistic The symbol is κ (kappa). Include a zero before the decimal point if the value is less than 1. Example:


The κ value indicating inter-observer reliability was 0.5.

Equal and “inequality” signs DO NOT insert spaces before and after the sign. Remove blank spaces on either sides of mathematical operators to adhere to our preferred format without blanks. The same is true for other equality and inequality expressions, eg, (P < .001) should be changed to (P<.001) and (n = 12) should be corrected to (n=12). For greater than or equal to and less than or equal to signs, insert a single symbol using MS Word (Mac shortcuts ≥: option+> ; ≤: option+<; Windows shortcuts ≥: ALT+8805 ; ≤: ALT+8804) DO NOT use an underlined greater than/less than symbol. Examples:




Greek letters in text Greek letters are used as per the AMA guidelines: Use of Greek letters rather than spelled-out words is preferred, unless common usage dictates otherwise (eg, tau protein). In titles, subtitles, headings, and at the beginning of sentences, the first non-Greek letter after a lowercase Greek letter should be capitalized. Examples:

Cronbach α


β-Blockers help control heart rate…

Currency Specify all currencies in US$. For amounts reported in non-US currency, the current exchange rate should be used to calculate the amount in US dollars, and that amount should be shown in parentheses. For example, “Each participant was rewarded with Amazon gift cards worth Can $5 (US $7.18) for their participation” If there are more than 10 instances of another currency presented, ask the author to add a blanket statement of the exchange rate from the currency they have mentioned to US$. For example, “A currency exchange rate of Can $1=US $0.72 is applicable.” For all currency measures, refer to the 11th edition of the AMA here: https://www.amamanualofstyle.com/view/10.1093/jama/9780190246556.001.0001/med-9780190246556-chapter-17-div2-34?rskey=z4zEI1&result=1 DO NOT use zeros after whole numbers of currency. US $99

Can $125.35


Aus $100 (Note: AMA says “A$” for Australian dollars, but since we use a space before the $, this would be confusing as “A $100”; therefore, we'll abbreviate to “Aus $”)

Complex equations In text, whenever possible, equations should be inserted using characters from the Symbols list of MS Word. Equations can be inserted within a paragraph (run-in with the text) or on a separate line. Do NOT use the equation editor/tools in Word. The special formatting will not be picked up by our scripts.

Simple equations that are kept in text should be indented and numbered (number in bold) in parenthesis after the equation itself. Criteria for numbering equations consecutively are as follows: If there are numerous equations (>3) in a manuscript, if equations are related to each other, or if the equations are referred to after initial presentation.


yi = Ci - ci (1)

Use spaces between all mathematical operators in complex equations (including “=”). Note in this case, “=” is functioning as an operator, it is not a statement of equality. In the case of “n=2,” no spaces are used as it is a statement of equality.

“Trending” towards significance We do not use “trending towards significance” or other variants.

For example, “There was a trend (P=.06) showing that…was significant”.

It's fair to say that there was a trend in something, but this must be followed up with ”…but these results were not statistically significant.“

Alternatively, it's best to simply state the results' significance and not use variations of “trend”.

# Material mínimo a incluir ## Minimum Standards of Reporting Checklist BMC Neuroscience advocates full and transparent reporting. Please ensure that your paper provides the information requested below where applicable. On submitting your paper you will be asked to confirm you have included this information, or give reasons for any instances where it is not made available.

Experimental design and statistics The following information should be included in the Methods section:

The exact sample size (n) for each experimental group/condition (as a number, not a range). Include details of a power analysis if done, or any other relevant considerations that determined the choice of sample size. For n < 6, individual data values should be shown rather than summary statistics alone.

A description of sample collection that enables the reader to understand whether the samples represent technical or biological replicates, and an explanation of inclusion/exclusion criteria if samples or organisms were excluded from the analysis.

How samples/ organisms were allocated to experimental groups and processed, and full details of the randomisation procedure used (if relevant).

For sample assessment by human investigators, a statement on whether the investigator was blinded to group assignment and outcome assessment, and how this blinding was achieved and evaluated (if relevant).

How many times each experiment shown was replicated and an indication of the extent of variation from experiment to experiment.

Information on the statistical methods and measures used. It should be clear whether the tests are one-sided or two-sided, whether there are adjustments for multiple comparisons, whether medians or means are being shown, whether error bars are standard deviations (SD), standard error of mean (SEM) or confidence intervals.

A justification for the appropriateness of statistical tests used to assess significance. Do the data meet the assumptions of the tests? Is there an estimate of variation within each group of data, and is the variance similar between groups that are being statistically compared?

In addition, information essential to interpreting the data presented should be made available in the figure and table legends.

## Journal Psicología

### Experimental Design:

Good experimental design features are a requirement of all manuscripts considered for publication. The overriding concern is that the design employed is such as to permit the aims of the study to be fully and efficiently achievable. Specifically, the following represents a listing of several of the more commonly employed good design features; many of these features are intended to enhance statistical power and through the control of extraneous variation. Avoidance of confounding (assuring that treatment effects are separable) Balance, counterbalance and crossover (negating temporal or learning effects) Blocking (the use of smaller more homogeneous blocks of experimental units) Use of covariate(s) (such as adjustment for differing initial or baseline values) Randomisation of treatment allocation (often, but not necessarily restricted) Single- or double-blinding (assuring independence of effects) Inclusion of controls or placebos (for normative or comparative purposes) Matched controls (for improved precision of comparisons)

### Sample Size (n) Considerations:

Sample sizes must always be clearly stated. They should be justifiable, and large enough to provide reliable results and inferences. In hierarchical designs, effective sample sizes at each level should be clearly evident. Case studies (n = 1) will be considered on their merits. Intervention studies with small sample size (n less than about 15) should be treated with appropriate caution. For example, in such situations, sensitivity may be compromised, inferences to a wider population may not be feasible, and nonparametric methods may be more appropriate. Other small sample studies will be assessed on their merits. Larger sample sizes should be subject to an investigation of their cost:benefit aspects, though it is recognised that in the study of rare events where incidence is low, large samples are frequently a necessity.Significance Level ( α ), P-value and Power: The minimum P-value to achieve significance (the chosen α) should be stated and justified before any data are collected. The commonly adopted α = 0.05 is not necessarily always appropriate. In particular, it is important to recognise that when several tests are being performed (not just in multiple comparisons), the likelihood of rejecting at least one true null hypothesis (a Type 1 error) is increased. Consideration should therefore be given to downward adjustment of the chosen α level(s) a priori. In addition, after analysis, it is informative to readers if authors report the exact P- value for any important results. Statistical power (probability of rejection of a false null hypothesis, or of not committing a Type 2 error) is affected by the chosen α level, sample size, inherent variability, and the real, but often unknown, value of the tested parameter under the alternate hypothesis (often referred to as the effect size). All of these should be considered. It is advisable to carry out at least an approximate power analysis for any investigation, where feasible. While it is not always necessary to report this in the manuscript itself, it is useful supportive information to include in the submission.

### Selection and Validity of Analytical Methods:

In most instances several analytical methods may be available for use, and it is not normally the case that one is correct and all others are wrong. One may be more appropriate, or more informative than another, and the choice of which to use lies with the author. In some cases it may be helpful to indicate the reason(s) for selection of one method in preference to another. For analysis of data, the European Journal of Applied Physiology has no specific preferred statistical software of choice. Authors are free to select whichever they prefer, but such selection should always be stated and referenced. Most parametric analyses are based on a variety of assumptions about the distribution of the data (or of the residuals after modelling). Some techniques are sensitive to departures from these assumptions, while others are robust. Authors should note the relevant assumptions for the method(s) they employ, and confirm their validity. If there is a degree of departure, this should be reported also and appropriate remedial action taken. This may necessitate a transformation of the data, application of an adjustment or correction factor, or a change in method. Failure to account for any such departures usually invalidates the method and any subsequent inferences. Disclosure of Variability, Uncertainty and Error: Authors are urged to accurately disclose measures of variability, uncertainty, measurement error etc. For variability of individual values, the standard deviation should be used; whereas for variability of mean values, the standard error should be used. Uncertainty should normally be expressed using either confidence intervals or limits of agreement. The disclosure of measurement error, and the concomitant number of significant digits used when reporting measured values, is an important adjunct to interpretation of the results.

## Nature

Every article that contains statistical testing should state the name of the statistical test, the n value for each statistical analysis, the comparisons of interest, a justification for the use of that test (including, for example, a discussion of the normality of the data when the test is appropriate only for normal data), the alpha level for all tests, whether the tests were one-tailed or two-tailed, and the actual P value for each test (not merely “significant” or “P < 0.05”). It should be clear what statistical test was used to generate every P value. Use of the word “significant” should always be accompanied by a P value; otherwise, use “substantial,” “considerable,” etc.

Data sets should be summarized with descriptive statistics, which should include the n value for each data set, a clearly labelled measure of centre (such as the mean or the median), and a clearly labelled measure of variability (such as standard deviation or range). Ranges are more appropriate than standard deviations or standard errors for small data sets. Graphs should include clearly labelled error bars. Authors must state whether a number that follows the ± sign is a standard error (s.e.m.) or a standard deviation (s.d.).

Authors must justify the use of a particular test and explain whether their data conform to the assumptions of the tests. Three errors are particularly common:

Multiple comparisons: When making multiple statistical comparisons on a single data set, authors should explain how they adjusted the alpha level to avoid an inflated Type I error rate, or they should select statistical tests appropriate for multiple groups (such as ANOVA rather than a series of t-tests). Normal distribution: Many statistical tests require that the data be approximately normally distributed; when using these tests, authors should explain how they tested their data for normality. If the data do not meet the assumptions of the test, then a non-parametric alternative should be used instead. Small sample size: When the sample size is small (less than about 10), authors should use tests appropriate to small samples or justify their use of large-sample tests.

## Ejemplos de reportes

ver reporte de distintos test estadísticos

Ver Ayuda estadística para estudiantes

## SAMPL Guidelines Ver SAMPL Guidelines

### Preliminary analyses • Identify any statistical procedures used to modify raw data before analysis. Examples include mathematically transforming continuous measurements to make distributions closer to the normal distribution, creating ratios or other derived variables, and collapsing continuous data into categorical data or combining categories.

## Guideline de reporte de estadísticas en una publicación

### Materials and Methods

Guideline 1. If in doubt, consult a statistician when you plan your study. Guideline 2. Define and justify a critical significance level appropriate to the goals of your study. Guideline 3. Identify your statistical methods, and cite them using textbooks or review papers. Cite separately comercial software you used to do your statistical analysis. Guideline 4. Control for multiple comparisons.

### Results

Guideline 5. Report variability using a standard deviation. Guideline 6. Report uncertainty about scientific importance using a confidence interval. Guideline 7. Report a precise P value. Guideline 8. Report a quantity so the number of digits is commensurate with scientific relevance.

### Discussion

Guideline 10. Interpret each main result by assessing the numerical bounds of the confidence interval and by considering the precise P value.

reporte_de_analisis_estadistico_en_revistas.txt · Última modificación: 2020/10/24 09:28 por admin